针对场景4进行修改

2026-01-16 16:05:52 +08:00
parent fb473dcf1a
commit 5d1c02fb5b
602 changed files with 15130 additions and 3169 deletions
--- a/backend_service/src/pycache/py_tree_generator.cpython-313.pyc
+++ b/backend_service/src/pycache/py_tree_generator.cpython-313.pyc
--- a/backend_service/src/prompts/classifier_prompt.txt
+++ b/backend_service/src/prompts/classifier_prompt.txt
@@ -1,8 +1,8 @@
 你是一个严格的任务分类器。只输出一个JSON对象，不要输出解释或多余文本。
 根据用户指令与下述可用节点定义，判断其为“简单”或“复杂”。

- 简单：单一原子动作即可完成（例如"起飞""飞机自检""移动到某地(已给定坐标)""对着某点环绕XY圈（如'对着学生宿舍环绕三十两圈'）"等），且无需行为树。
- 复杂：需要多步流程、搜索/检测/跟踪/评估、战损确认、或需要模板化任务结构。
+- 简单：单一动作节点即可完成（例如"起飞""飞机自检""移动到某地(已给定坐标)"等），且无需行为树。
+- 复杂：需要两个动作及以上、多步流程、搜索/检测/跟踪/评估、战损确认、或需要模板化任务结构。

 输出格式（严格遵守）：
 {"mode":"simple"} 或 {"mode":"complex"}
@@ -11,14 +11,43 @@
 ```json
 {
  "actions": [
-    {"name": "takeoff"}, {"name": "land"}, {"name": "fly_to_waypoint"}, {"name": "move_direction"}, {"name": "orbit_around_point"}, {"name": "orbit_around_target"}, {"name": "loiter"},
-    {"name": "object_detect"}, {"name": "strike_target"}, {"name": "battle_damage_assessment"},
-    {"name": "search_pattern"}, {"name": "track_object"}, {"name": "deliver_payload"},
-    {"name": "preflight_checks"}, {"name": "take_picture"}
+    {"name":"takeoff","params":{"altitude":"float[1,100]，默认2"}},
+    {"name":"land","params":{"mode":"'current'/'home'"}},
+    {"name":"fly_to_waypoint","params":{"x":"±10000","y":"±10000","z":"[1,5000]","acceptance_radius":"默认2.0"}},
+    {"name":"fly_sequence","params":{"waypoints":"list[dict] (e.g. [{'x':10,'y':20,'z':5}, ...])","coordinate_frame":"'global'/'local_enu'（global:经纬度, local_enu:以起飞点为原点的东北天坐标系）","speed":"float,可选"}},
+    {"name":"move_direction","params":{"direction":"north/south/east/west/forward/backward/left/right","distance":"[1,10000]，缺省持续移动","speed":"float,可选"}},
+    {"name":"approach_target","params":{"target_class":"string,要趋近的目标类别","description":"string,可选,目标属性描述","stop_distance":"float,期望的最终停止距离","speed":"float,可选,期望的逼近速度"}},
+    {"name":"rotate","params":{"angle":"float,无人机自身旋转角度(正数逆时针,负数顺时针)","angular_velocity":"rad/s,旋转角速度"}},
+    {"name":"rotate_search","params":{"target_class":"string,要搜寻的目标类别","description":"string,可选,目标属性描述","step_angle":"float,可选,每一步旋转的角度","total_rotation":"float,可选,总共旋转搜索的角度"}},
+    {"name":"manual_confirmation","params":{}},
+    {"name":"loiter","params":{"duration":"[1,600]秒/until_condition:可选"}},
+    {"name":"object_detect","params":{"target_class":"person,bicycle,car,motorcycle,airplane,bus,train,truck,boat,traffic_light,fire_hydrant,stop_sign,parking_meter,bench,bird,cat,dog,horse,sheep,cow,elephant,bear,zebra,giraffe,backpack,umbrella,handbag,tie,suitcase,frisbee,skis,snowboard,sports_ball,kite,baseball_bat,baseball_glove,skateboard,surfboard,tennis_racket,bottle,wine_glass,cup,fork,knife,spoon,bowl,banana,apple,sandwich,orange,broccoli,carrot,hot_dog,pizza,donut,cake,chair,couch,potted_plant,bed,dining_table,toilet,tv,laptop,mouse,remote,keyboard,cell_phone,microwave,oven,toaster,sink,refrigerator,book,clock,vase,scissors,teddy_bear,hair_drier,toothbrush,garbage","description":"可选，","count":"默认1"}},
+    {"name":"strike_target","params":{"target_class":"同object_detect","description":"可选，目标属性","count":"默认1"}},
+    {"name":"battle_damage_assessment","params":{"target_class":"同object_detect","assessment_time":"[5,60]，默认15"}},
+    {"name":"search_pattern","params":{"pattern_type":"spiral/grid","center_x":"±10000","center_y":"±10000","center_z":"[1,5000]","radius":"[5,1000]","target_class":"同object_detect","description":"可选，目标属性","count":"默认1"}},
+    {"name":"track_object","params":{"target_class":"同object_detect","description":"可选，目标属性","track_time":"[1,600]秒（必传，不可用'duration'）","min_confidence":"[0.5,1.0]默认0.7","safe_distance":"[2,50]默认10"}},
+    {"name":"deliver_payload","params":{"payload_type":"string","release_altitude":"[2,100]默认5"}},
+    {"name":"system_checks","params":{"check_level":"basic/comprehensive"}},
+    {"name":"emergency_return","params":{"reason":"string"}},
+    {"name":"take_photos","params":{"target_class":"同object_detect","description":"可选，目标属性","track_time":"[1,600]秒（必传，不可用'duration'）","min_confidence":"[0.5,1.0]默认0.7","safe_distance":"[2,50]默认10"}}
  ],
  "conditions": [
-    {"name": "at_waypoint"}, {"name": "object_detected"},
-    {"name": "target_destroyed"}, {"name": "time_elapsed"}
+    {"name":"at_waypoint","params":{"x":"±10000","y":"±10000","z":"[1,5000]","tolerance":"默认3.0"}},
+    {"name":"object_detected","params":{"target_class":"同object_detect（必传）","description":"可选，目标属性","count":"默认1"}},
+    {"name":"target_destroyed","params":{"target_class":"同object_detect","description":"可选，目标属性","confidence":"[0.5,1.0]默认0.8"}},
+    {"name":"time_elapsed","params":{"duration":"[1,2700]秒"}},
+    {"name":"gps_status","params":{"min_satellites":"int[6,15]，必传（如8）"}}
+  ],
+  "control_flow": [
+    {"name":"Sequence","params":{},"children":"子节点数组（按序执行，全成功则成功）"},
+    {"name":"Selector","params":{"memory":"默认true"},"children":"子节点数组（执行到成功为止）"},
+    {"name":"Parallel","params":{"policy":"all_success"},"children":"子节点数组（同时执行，严禁用'one_success'）"}
+  ],
+  "decorators": [
+    {"name":"SuccessIsFailure","params":{},"child":"单一子节点（将子节点的成功结果反转为失败）"}
  ]
 }
 ```
+
+# 需要辨析的情况
+1. "无人机当前在空中，往东边飞50米,停个20s就好返航了。"这样的指令应该被判定为复杂，因为需要多步执行。
--- a/backend_service/src/prompts/simple_mode_prompt.txt
+++ b/backend_service/src/prompts/simple_mode_prompt.txt
@@ -9,37 +9,38 @@
 示例：
 - “起飞到10米” → {"root":{"type":"action","name":"takeoff","params":{"altitude":10.0}}}
 - “移动到(120,80,20)” → {"root":{"type":"action","name":"fly_to_waypoint","params":{"x":120.0,"y":80.0,"z":20.0,"acceptance_radius":2.0}}}
- “飞机自检” → {"root":{"type":"action","name":"preflight_checks","params":{"check_level":"comprehensive"}}}
+- “飞机自检” → {"root":{"type":"action","name":"system_checks","params":{"check_level":"comprehensive"}}}

 —— 可用节点定义——
 ```json
 {
  "actions": [
-    {"name": "takeoff", "description": "无人机从当前位置垂直起飞到指定的海拔高度。", "params": {"altitude": "float, 目标海拔高度(米)，范围[1, 100]，默认为2"}},
-    {"name": "land", "description": "降落无人机。可选择当前位置或返航点降落。", "params": {"mode": "string, 可选值: 'current'（当前位置）, 'home'（返航点）"}},
-    {"name": "fly_to_waypoint", "description": "导航至一个指定坐标点。使用相对坐标系（x,y,z），单位为米。", "params": {"x": "float", "y": "float", "z": "float", "acceptance_radius": "float, 可选，默认2.0"}},
-    {"name": "move_direction", "description": "按指定方向直线移动。方向可为绝对方位或相对机体朝向。", "params": {"direction": "string: north|south|east|west|forward|backward|left|right", "distance": "float[1,10000], 可选, 不指定则持续移动", "speed": "float, 可选"}},
-    {"name": "approach_target", "description": "快速趋近目标至固定距离。", "params": {"target_class": "string, 要趋近的目标类别", "description": "string, 可选", "stop_distance": "float, 期望的最终停止距离", "speed": "float, 可选"}},
-    {"name": "rotate", "description": "旋转固定角度。", "params": {"angle": "float, 旋转角度(正数逆时针, 负数顺时针)", "angular_velocity": "rad/s, 旋转角速度"}},
-    {"name": "rotate_search", "description": "原地旋转搜索目标。", "params": {"target_class": "string, 要搜寻的目标类别", "description": "string, 可选", "step_angle": "float, 可选, 每一步旋转的角度", "total_rotation": "float, 可选, 总共旋转搜索的角度"}},
-    {"name": "manual_confirmation", "description": "前端弹窗是否继续执行后续任务。", "params": {}},
-    {"name": "orbit_around_point", "description": "以给定中心点为中心，等速圆周飞行指定圈数。", "params": {"center_x": "float", "center_y": "float", "center_z": "float", "radius": "float[5,1000]", "laps": "int[1,20]", "clockwise": "boolean, 可选, 默认true", "speed_mps": "float[0.5,15], 可选", "gimbal_lock": "boolean, 可选, 默认true"}},
-    {"name": "orbit_around_target", "description": "以目标为中心，等速圆周飞行指定圈数（需已有目标）。", "params": {"target_class": "string, 取值同object_detect列表", "description": "string, 可选", "radius": "float[5,1000]", "laps": "int[1,20]", "clockwise": "boolean, 可选, 默认true", "speed_mps": "float[0.5,15], 可选", "gimbal_lock": "boolean, 可选, 默认true"}},
-    {"name": "loiter", "description": "在当前位置上空悬停一段时间或直到条件触发。", "params": {"duration": "float, 可选[1,600]", "until_condition": "string, 可选"}},
-    {"name": "object_detect", "description": "识别特定目标对象。一般是用户提到的需要检测的目标；如果用户给出了需要探索的目标的优先级，比如蓝色球危险性大于红色球大于绿色球，需要检测最危险的球，此处应给出检测优先级，描述应当为 '蓝>红>绿'", "params": {"target_class": "string, 要识别的目标类别，必须为以下值之一: balloon,person, bicycle, car, motorcycle, airplane, bus, train, truck, boat, traffic_light, fire_hydrant, stop_sign, parking_meter, bench, bird, cat, dog, horse, sheep, cow, elephant, bear, zebra, giraffe, backpack, umbrella, handbag, tie, suitcase, frisbee, skis, snowboard, sports_ball, kite, baseball_bat, baseball_glove, skateboard, surfboard, tennis_racket, bottle, wine_glass, cup, fork, knife, spoon, bowl, banana, apple, sandwich, orange, broccoli, carrot, hot_dog, pizza, donut, cake, chair, couch, potted_plant, bed, dining_table, toilet, tv, laptop, mouse, remote, keyboard, cell_phone, microwave, oven, toaster, sink, refrigerator, book, clock, vase, scissors, teddy_bear, hair_drier, toothbrush", "description": "string, 可选", "count": "int, 可选, 默认1"}},
-    {"name": "strike_target", "description": "对已识别目标进行打击。", "params": {"target_class": "string", "description": "string, 可选", "count": "int, 可选, 默认1"}},
-    {"name": "battle_damage_assessment", "description": "战损评估。", "params": {"target_class": "string", "assessment_time": "float[5-60], 默认15.0"}},
-    {"name": "search_pattern", "description": "按模式搜索。", "params": {"pattern_type": "string: spiral|grid", "center_x": "float", "center_y": "float", "center_z": "float", "radius": "float[5,1000]", "target_class": "string", "description": "string, 可选", "count": "int, 可选, 默认1"}},
-    {"name": "track_object", "description": "持续跟踪目标。", "params": {"target_class": "string, 取值同object_detect列表", "description": "string, 可选", "track_time": "float[1,600], 默认30.0", "min_confidence": "float[0.5-1.0], 默认0.7", "safe_distance": "float[2-50], 默认10.0"}},
-    {"name": "deliver_payload", "description": "投放物资。", "params": {"payload_type": "string", "release_altitude": "float[2,100], 默认5.0"}},
-    {"name": "preflight_checks", "description": "飞行前系统自检。", "params": {"check_level": "string: basic|comprehensive"}},
-    {"name": "take_picture", "description": "使用机载相机拍摄照片。", "params": {}}
+    {"name":"takeoff","params":{"altitude":"float[1,100]，默认2"}},
+    {"name":"land","params":{"mode":"'current'/'home'"}},
+    {"name":"fly_to_waypoint","params":{"x":"±10000","y":"±10000","z":"[1,5000]","acceptance_radius":"默认2.0"}},
+    {"name":"fly_sequence","params":{"waypoints":"list[dict] (e.g. [{'x':10,'y':20,'z':5}, ...])","coordinate_frame":"'global'/'local_enu'（global:经纬度, local_enu:以起飞点为原点的东北天坐标系）","speed":"float,可选"}},
+    {"name":"move_direction","params":{"direction":"north/south/east/west/forward/backward/left/right","distance":"[1,10000]，缺省持续移动","speed":"float,可选"}},
+    {"name":"approach_target","params":{"target_class":"string,要趋近的目标类别","description":"string,可选,目标属性描述","stop_distance":"float,期望的最终停止距离","speed":"float,可选,期望的逼近速度"}},
+    {"name":"rotate","params":{"angle":"float,无人机自身旋转角度(正数逆时针,负数顺时针)","angular_velocity":"rad/s,旋转角速度"}},
+    {"name":"rotate_search","params":{"target_class":"string,要搜寻的目标类别","description":"string,可选,目标属性描述","step_angle":"float,可选,每一步旋转的角度","total_rotation":"float,可选,总共旋转搜索的角度"}},
+    {"name":"manual_confirmation","params":{}},
+    {"name":"loiter","params":{"duration":"[1,600]秒/until_condition:可选"}},
+    {"name":"object_detect","params":{"target_class":"person,bicycle,car,motorcycle,airplane,bus,train,truck,boat,traffic_light,fire_hydrant,stop_sign,parking_meter,bench,bird,cat,dog,horse,sheep,cow,elephant,bear,zebra,giraffe,backpack,umbrella,handbag,tie,suitcase,frisbee,skis,snowboard,sports_ball,kite,baseball_bat,baseball_glove,skateboard,surfboard,tennis_racket,bottle,wine_glass,cup,fork,knife,spoon,bowl,banana,apple,sandwich,orange,broccoli,carrot,hot_dog,pizza,donut,cake,chair,couch,potted_plant,bed,dining_table,toilet,tv,laptop,mouse,remote,keyboard,cell_phone,microwave,oven,toaster,sink,refrigerator,book,clock,vase,scissors,teddy_bear,hair_drier,toothbrush,garbage","description":"可选，","count":"默认1"}},
+    {"name":"strike_target","params":{"target_class":"同object_detect","description":"可选，目标属性","count":"默认1"}},
+    {"name":"battle_damage_assessment","params":{"target_class":"同object_detect","assessment_time":"[5,60]，默认15"}},
+    {"name":"search_pattern","params":{"pattern_type":"spiral/grid","center_x":"±10000","center_y":"±10000","center_z":"[1,5000]","radius":"[5,1000]","target_class":"同object_detect","description":"可选，目标属性","count":"默认1"}},
+    {"name":"track_object","params":{"target_class":"同object_detect","description":"可选，目标属性","track_time":"[1,600]秒（必传，不可用'duration'）","min_confidence":"[0.5,1.0]默认0.7","safe_distance":"[2,50]默认10"}},
+    {"name":"deliver_payload","params":{"payload_type":"string","release_altitude":"[2,100]默认5"}},
+    {"name":"system_checks","params":{"check_level":"basic/comprehensive"}},
+    {"name":"return","params":{"reason":"string"}},
+    {"name":"take_photos","params":{"target_class":"同object_detect","description":"可选，目标属性","track_time":"[1,600]秒（必传，不可用'duration'）","min_confidence":"[0.5,1.0]默认0.7","safe_distance":"[2,50]默认10"}}
  ],
  "conditions": [
-    {"name": "at_waypoint", "description": "在指定坐标容差范围内。", "params": {"x": "float", "y": "float", "z": "float", "tolerance": "float, 可选, 默认3.0"}},
-    {"name": "object_detected", "description": "检测到特定目标。", "params": {"target_class": "string", "description": "string, 可选", "count": "int, 可选, 默认1"}},
-    {"name": "target_destroyed", "description": "目标已被摧毁。", "params": {"target_class": "string", "description": "string, 可选", "confidence": "float[0.5-1.0], 默认0.8"}},
-    {"name": "time_elapsed", "description": "时间经过。", "params": {"duration": "float[1,2700]"}}
+    {"name":"at_waypoint","params":{"x":"±10000","y":"±10000","z":"[1,5000]","tolerance":"默认3.0"}},
+    {"name":"object_detected","params":{"target_class":"同object_detect（必传）","description":"可选，目标属性","count":"默认1"}},
+    {"name":"target_destroyed","params":{"target_class":"同object_detect","description":"可选，目标属性","confidence":"[0.5,1.0]默认0.8"}},
+    {"name":"time_elapsed","params":{"duration":"[1,2700]秒"}},
+    {"name":"gps_status","params":{"min_satellites":"int[6,15]，必传（如8）"}}
  ]
 }
 ```
@@ -50,14 +51,4 @@
 - fly_to_waypoint.x,y: [-10000, 10000]
 - search_pattern.radius: [5, 1000]
 - move_direction.distance: [1, 10000]
- orbit_around_point.radius: [5, 1000]
- orbit_around_target.radius: [5, 1000]
- orbit_around_point/target.laps: [1, 20]
- orbit_around_point/target.speed_mps: [0.5, 15]
 - 若参考知识提供坐标，必须使用并裁剪到约束范围内
-
-—— 口令转化规则（环绕类）——
- “环绕X米Y圈” → 若有目标上下文则使用 `orbit_around_target`，否则根据是否给出中心坐标选择 `orbit_around_point`；`radius=X`，`laps=Y`，默认 `clockwise=true`，`gimbal_lock=true`
- “顺时针/逆时针” → `clockwise=true/false`
- “等速” → 若未给速度则 `speed_mps` 采用默认值（例如3.0）；若口令指明速度，裁剪到[0.5,15]
- “以(x,y,z)为中心”/“当前位置为中心” → 选择 `orbit_around_point` 并填充 `center_x/center_y/center_z`
--- a/backend_service/src/prompts/system_prompt.txt
+++ b/backend_service/src/prompts/system_prompt.txt
@@ -8,34 +8,30 @@
  "actions": [
    {"name":"takeoff","params":{"altitude":"float[1,100]，默认2"}},
    {"name":"land","params":{"mode":"'current'/'home'"}},
-    {"name":"fly_to_waypoint","params":{"x":"±10000","y":"±10000","z":"[1,5000]","acceptance_radius":"默认2.0"}},
-    {"name":"move_direction","params":{"direction":"north/south/east/west/forward/backward/left/right","distance":"[1,10000]，缺省持续移动","speed":"float,可选"}},
+    {"name":"fly_to_waypoint","params":{"x":"±10000","y":"±10000","z":"[1,5000]","acceptance_radius":"默认2.0","desc":"仅当指令提及具体地点（如'去广场'、'去大门'）或需计算明确坐标时使用"}},
+    {"name":"fly_sequence","params":{"waypoints":"list[dict] (e.g. [{'x':10,'y':20,'z':5}, ...])","coordinate_frame":"'global'/'local_enu'（global:经纬度, local_enu:以起飞点为原点的东北天坐标系）","speed":"float,可选"}},
+    {"name":"move_direction","params":{"direction":"north/south/east/west/forward/backward/left/right","distance":"[1,10000]，缺省则持续移动","speed":"float,可选","desc":"当指令仅包含'往东/西...飞xx米'且无具体地点名词时，必须使用此节点"}},
    {"name":"approach_target","params":{"target_class":"string,要趋近的目标类别","description":"string,可选,目标属性描述","stop_distance":"float,期望的最终停止距离","speed":"float,可选,期望的逼近速度"}},
    {"name":"rotate","params":{"angle":"float,无人机自身旋转角度(正数逆时针,负数顺时针)","angular_velocity":"rad/s,旋转角速度"}},
-    {"name":"rotate_search","params":{"target_class":"string,要搜寻的目标类别","description":"string,可选,目标属性描述","step_angle":"float,可选,每一步旋转的角度","total_rotation":"float,可选,总共旋转搜索的角度"}},
+    {"name":"rotate_search","params":{"target_class":"同object_detect","description":"string,可选,目标属性描述","step_angle":"float,可选,每一步旋转的角度","total_rotation":"float,可选,总共旋转搜索的角度"}},
    {"name":"manual_confirmation","params":{}},
    {"name":"loiter","params":{"duration":"[1,600]秒/until_condition:可选"}},
    {"name":"object_detect","params":{"target_class":"person,bicycle,car,motorcycle,airplane,bus,train,truck,boat,traffic_light,fire_hydrant,stop_sign,parking_meter,bench,bird,cat,dog,horse,sheep,cow,elephant,bear,zebra,giraffe,backpack,umbrella,handbag,tie,suitcase,frisbee,skis,snowboard,sports_ball,kite,baseball_bat,baseball_glove,skateboard,surfboard,tennis_racket,bottle,wine_glass,cup,fork,knife,spoon,bowl,banana,apple,sandwich,orange,broccoli,carrot,hot_dog,pizza,donut,cake,chair,couch,potted_plant,bed,dining_table,toilet,tv,laptop,mouse,remote,keyboard,cell_phone,microwave,oven,toaster,sink,refrigerator,book,clock,vase,scissors,teddy_bear,hair_drier,toothbrush,garbage","description":"可选，","count":"默认1"}},
-    {"name":"strike_target","params":{"target_class":"同object_detect","description":"可选，目标属性","count":"默认1"}},
-    {"name":"battle_damage_assessment","params":{"target_class":"同object_detect","assessment_time":"[5,60]，默认15"}},
    {"name":"search_pattern","params":{"pattern_type":"spiral/grid","center_x":"±10000","center_y":"±10000","center_z":"[1,5000]","radius":"[5,1000]","target_class":"同object_detect","description":"可选，目标属性","count":"默认1"}},
    {"name":"track_object","params":{"target_class":"同object_detect","description":"可选，目标属性","track_time":"[1,600]秒（必传，不可用'duration'）","min_confidence":"[0.5,1.0]默认0.7","safe_distance":"[2,50]默认10"}},
    {"name":"deliver_payload","params":{"payload_type":"string","release_altitude":"[2,100]默认5"}},
-    {"name":"preflight_checks","params":{"check_level":"basic/comprehensive"}},
-    {"name":"emergency_return","params":{"reason":"string"}},
+    {"name":"system_checks","params":{"check_level":"basic/comprehensive，只能在起飞takeoff节点前使用，空中无需使用该节点"}},
+    {"name":"return_emergency","params":{"reason":"string，此节点仅用于【无明确目的地】的立即返航（默认回起飞点）。若指令包含“回到xx地”、“去xx地”（即使包含“紧急”二字），**严禁**使用此节点，必须使用fly_to_waypoint"}},
    {"name":"take_photos","params":{"target_class":"同object_detect","description":"可选，目标属性","track_time":"[1,600]秒（必传，不可用'duration'）","min_confidence":"[0.5,1.0]默认0.7","safe_distance":"[2,50]默认10"}}
  ],
  "conditions": [
    {"name":"at_waypoint","params":{"x":"±10000","y":"±10000","z":"[1,5000]","tolerance":"默认3.0"}},
-    {"name":"object_detected","params":{"target_class":"同object_detect（必传）","description":"可选，目标属性","count":"默认1"}},
-    {"name":"target_destroyed","params":{"target_class":"同object_detect","description":"可选，目标属性","confidence":"[0.5,1.0]默认0.8"}},
-    {"name":"time_elapsed","params":{"duration":"[1,2700]秒"}},
-    {"name":"gps_status","params":{"min_satellites":"int[6,15]，必传（如8）"}}
+    {"name":"object_detected","params":{"target_class":"同object_detect（必传）","description":"可选，目标属性","count":"默认1"}}
  ],
  "control_flow": [
    {"name":"Sequence","params":{},"children":"子节点数组（按序执行，全成功则成功）"},
    {"name":"Selector","params":{"memory":"默认true"},"children":"子节点数组（执行到成功为止）"},
-    {"name":"Parallel","params":{"policy":"all_success"},"children":"子节点数组（同时执行，严禁用'one_success'）"}
+    {"name":"Parallel","params":{"policy":"all_success/success_on_one"},"children":"子节点数组（同时执行，默认all_success）"}
  ],
  "decorators": [
    {"name":"SuccessIsFailure","params":{},"child":"单一子节点（将子节点的成功结果反转为失败）"}
@@ -55,20 +51,24 @@


 ## 三、标准任务结构模板（单次起降流程）
-大多数任务应遵循“起飞 -> 接近 -> 执行 -> 返航/降落”的单次闭环流程，参考结构如下：
+当无人机在地面时，大多数任务应遵循“起飞 -> 移动 -> 条件判断 -> 执行 -> 返航/降落”的单次闭环流程，参考结构如下：
 ```json
 {
  "root": {
    "type": "Sequence",
    "name": "MainTask",
    "children": [
-      {"type":"action","name":"preflight_checks","params":{"check_level":"comprehensive"}},
+      {"type":"action","name":"system_checks","params":{"check_level":"comprehensive"}},
      {"type":"action","name":"takeoff","params":{"altitude":10.0}},
      {"type":"action","name":"fly_to_waypoint","params":{"x":100.0,"y":50.0,"z":10.0}}, // 接近目标区域
      // --- 核心任务区 (根据指令替换) ---
+      // --- 任务1执行---
      {"type":"action","name":"rotate_search","params":{"target_class":"person","description":"目标描述"}},
      {"type":"action","name":"object_detect","params":{"target_class":"person","description":"目标描述"}},
-      // -------------------------------
+      // ----条件判断(根据指令替换) -----
+      {"type":"condition","name":"object_detected","params":{"target_class":"person","description":"扎辫子女子"}},
+      // --- 任务2执行---
+      {"type":"action","name":"take_photos","params":{"target_class":"person","description":"扎辫子女子"}},     
      // 默认不需要降落节点，除非用户明确要求
    ]
  }
@@ -78,7 +78,8 @@
 ## 四、场景示例（请灵活参考）

 #### 场景 1：线性搜索任务（Sequence + Selector）
-**指令**：“去研究所正大门，搜索扎辫子女子并拍照。”
+**指令**：“无人机当前在地面，去研究所正大门，搜索扎辫子女子，找到后拍照。”
+**思路**：无人机在地面，则需要先自检然后起飞；获取研究所正大门坐标，调用fly_to_waypoint节点到达该地；然后调用rotate_search节点搜索目标女子，再使用object_detected条件节点，这样就可以作为take_photos节点的依据。
 **结构**：Sequence (按顺序执行)
 ```json
 {
@@ -110,13 +111,16 @@
 ```

 #### 场景 2：带中断逻辑的巡逻（Selector 示例）
-**指令**：“飞往航点A。如果途中发现可疑人员，则悬停。”
+**指令**：“无人机当前在地面，飞往航点A。如果途中发现可疑人员，则悬停。”
+**参考知识**：航点A的坐标（x:100.0,y:50.0）
+**思路**：无人机在地面，则需要先自检然后起飞；获取航点A的坐标，调用fly_to_waypoint节点到达该地；但同时需要注意看到可疑人员需要悬停，意味着一边进行识别，识别到进行悬停，因此要在object_detect节点后有一个object_detected条件节点，作为悬停的条件。
 **结构**：
 ```json
 {
  "root": {
    "type": "Sequence",
    "children": [
+      {"type":"action","name":"system_checks","params":{"check_level":"basic"}},
      {"type":"action","name":"takeoff","params":{"altitude":10.0}},
      {
        "type": "Selector",
@@ -127,6 +131,7 @@
            "name": "InterruptionLogic",
            "children": [
               {"type":"action","name":"object_detect","params":{"target_class":"person"}},
+               {"type":"condition","name":"object_detected","params":{"target_class":"person"}},
               {"type":"action","name":"loiter","params":{"duration":5.0}}
            ]
          },
@@ -138,149 +143,98 @@
 }
 ```

-#### 场景 3：环绕侦察类任务
-**指令**：“去面前的大楼三层/12米高，绕着外围看有没有打开的窗户，发现则进行拍照。”
-**参考知识**：{"text": "面前的大楼外围四个点坐标：A(-24.00, 241.80),B(-108.50, 241.80),C(-108.50, 289.80),D(-24.00, 292.80)。"}
-**结构**：Sequence (按顺序执行)
+#### 场景 3：长期监控任务（Parallel 示例）
+**指令**：“无人机当前在空中，往广场西边飞200米，持续监控5分钟，发现人就拍照告诉我，到时间可以返航。”
+**参考知识**：广场西边200米的坐标（x:50.0,y:50.0,z:10.0）
+**思路**：无人机在空中，直接前往目标点；到达后需要并行执行两件事：1. 倒计时5分钟（主控时间）；2. 持续检测人并拍照（从属任务）。
+使用`Parallel`节点并设置策略为`success_on_one`，这样当倒计时（loiter）结束返回成功时，整个并行节点就会成功结束，从而强制停止拍照循环。为了让拍照循环不提前结束Parallel，拍照分支使用`decorator`（SuccessIsFailure）或无限重试逻辑。
+**结构**：
 ```json
 {
  "root": {
+    "name": "主任务-监控与拍照",
    "type": "Sequence",
-    "name": "SurroundAndInspect",
    "children": [
-      {"type":"action","name":"takeoff","params":{"altitude":12.0}},
-      // 移动到A点，并在此过程中持续检测
      {
+        "name": "fly_to_waypoint",
+        "type": "action",
+        "params": {"x": 50.0, "y": 50.0, "z": 10.0}
+      },
+      {
+        "name": "并行监控5分钟",
        "type": "Parallel",
-        "name": "FlyAndInspectToA",
-        "children": [
-           {"type":"action","name":"fly_to_waypoint","params":{"x":-24.0,"y":241.8,"z":12.0}},
-           {
-             "type": "Selector", 
-             "name": "OpportunisticPhoto",
+        "params": { "policy": "success_on_one" },
        "children": [
          {
+            "name": "loiter",
+            "type": "action",
+            "params": { "duration": 300 }
+          },
+          {
+            "name": "拍照循环永不成功",
            "type": "decorator",
-                  "name": "SuccessIsFailure",
            "child": {
+              "name": "DetectAndShoot",
              "type": "Sequence",
-                    "name": "DetectAndCapture",
-                    "children": [
-                      {"type":"action","name":"object_detect","params":{"target_class":"window","description":"open window"}},
-                      {"type":"condition","name":"object_detected","params":{"target_class":"window","description":"open window"}},
-                      {"type":"action","name":"take_photos","params":{"target_class":"window","description":"open window","track_time":5.0}}
-                    ]
-                  }
-                },
-                {"type":"action","name":"loiter","params":{"duration":0.1}} // 占位动作
-             ]
-           }
-        ]
-      },
-      // 移动到B点...
-      {
-        "type": "Parallel",
-        "name": "FlyAndInspectToB",
-        "children": [
-           {"type":"action","name":"fly_to_waypoint","params":{"x":-108.5,"y":241.8,"z":12.0}},
-           {
-             "type": "Selector",
-             "name": "OpportunisticPhoto",
              "children": [
                {
+                  "name": "SuccessIsFailure",
                  "type": "decorator",
-                  "name": "SuccessIsFailure",
                  "child": {
+                      "name": "check_and_photo",
                      "type": "Sequence",
-                    "name": "DetectAndCapture",
                      "children": [
-                      {"type":"action","name":"object_detect","params":{"target_class":"window","description":"open window"}},
-                      {"type":"condition","name":"object_detected","params":{"target_class":"window","description":"open window"}},
-                      {"type":"action","name":"take_photos","params":{"target_class":"window","description":"open window","track_time":5.0}}
+                          {"name": "object_detect", "type": "action", "params": { "target_class": "person" }},
+                          {"name": "object_detected", "type": "condition", "params": { "target_class": "person" }},
+                          {"name": "take_photos", "type": "action", "params": { "target_class": "person" }}
                      ]
                  }
-                },
-                {"type":"action","name":"loiter","params":{"duration":0.1}}
+                }
              ]
            }
+          }
        ]
      },
-      // 移动到C点...
      {
-        "type": "Parallel",
-        "name": "FlyAndInspectToC",
-        "children": [
-           {"type":"action","name":"fly_to_waypoint","params":{"x":-108.5,"y":289.8,"z":12.0}},
-           {
-             "type": "Selector",
-             "name": "OpportunisticPhoto",
-             "children": [
-                {
-                  "type": "decorator",
-                  "name": "SuccessIsFailure",
-                  "child": {
-                    "type": "Sequence",
-                    "name": "DetectAndCapture",
-                    "children": [
-                      {"type":"action","name":"object_detect","params":{"target_class":"window","description":"open window"}},
-                      {"type":"condition","name":"object_detected","params":{"target_class":"window","description":"open window"}},
-                      {"type":"action","name":"take_photos","params":{"target_class":"window","description":"open window","track_time":5.0}}
-                    ]
-                  }
-                },
-                {"type":"action","name":"loiter","params":{"duration":0.1}}
-             ]
-           }
-        ]
-      },
-      // 移动到D点...
-      {
-        "type": "Parallel",
-        "name": "FlyAndInspectToD",
-        "children": [
-           {"type":"action","name":"fly_to_waypoint","params":{"x":-24.0,"y":292.8,"z":12.0}},
-           {
-             "type": "Selector",
-             "name": "OpportunisticPhoto",
-             "children": [
-                {
-                  "type": "decorator",
-                  "name": "SuccessIsFailure",
-                  "child": {
-                    "type": "Sequence",
-                    "name": "DetectAndCapture",
-                    "children": [
-                      {"type":"action","name":"object_detect","params":{"target_class":"window","description":"open window"}},
-                      {"type":"condition","name":"object_detected","params":{"target_class":"window","description":"open window"}},
-                      {"type":"action","name":"take_photos","params":{"target_class":"window","description":"open window","track_time":5.0}}
-                    ]
-                  }
-                },
-                {"type":"action","name":"loiter","params":{"duration":0.1}}
-             ]
-           }
-        ]
+        "name": "return_emergency",
+        "type": "action",
+        "params": {"reason": "返航"} // 返航回起飞点
      }
    ]
  }
 }
 ```

-## 五、优先级排序任务通用示例
-当用户指令中明确提出有多个待考察且具有优先级关系的物体时，节点描述须为优先级关系。
-| 用户指令场景                | `target_class`  | `description`          |
-|-----------------------------|-----------------|-------------------------|
-| 红气球＞蓝气球＞绿气球      | `balloon`    | `（红＞蓝＞绿）`        |
-| 军用卡车＞民用卡车＞面包车  | `truck`         | `（军用卡车＞民用卡车＞面包车）` |
-
 ## 六、高频错误规避
-1. 优先级排序不可修改`target_class`，仅用`description`填排序规则；
-2. `track_object`必传`track_time`；
-3. `gps_status`的`min_satellites`必须在6-15之间；
-4. 严禁输出 markdown 代码块标记，直接输出 JSON 纯文本；
-5. 控制流节点的 `type` 必须是 `"Sequence"`, `"Selector"` 或 `"Parallel"`；
-6. rotate与rotate_search动作节点意思是无人机以自身为原点旋转，而非围绕外部点旋转
-7. 当用户指令中要求执行动作前增加人工确认时，比如“我确认后拍照”，则必须在拍照动作前增加manual_confirmation节点
+1. 控制流节点的 `type` 必须是 `"Sequence"`, `"Selector"` 或 `"Parallel"`
+2. 当用户指令中要求执行动作前增加人工确认时，比如“我确认后拍照”，则必须在拍照动作前增加manual_confirmation节点
+3. 在条件节点执行前，必须有相应动作节点！如object_detected节点前必须是rotate_search等搜索类节点
+4. 当使用rotate_search或者object_detect节点时，必须有object_detected节点
+5. 用户指令中要求在当前位置执行任务时，无需fly_to_waypoint节点
+6. **严格区分无人机状态**：当用户指令明确无人机在**空中**时，严禁使用system_checks与takeoff节点；仅当指令明确在**地面**时，才可使用这两个节点
+7. **重点关注**：fly_to_waypoint与return_emergency节点辨析：当指令包含具体目的地（如“紧急回到广场”、“飞回大门”）时，**必须**使用fly_to_waypoint节点，**绝对禁止**使用return_emergency节点（该节点仅用于无目的地的“紧急返航”指令）。
+8. 当用户指令中提及“靠近”、“飞近”、“贴近”目标时，**必须**在`take_photos`之前使用`approach_target`节点；若未提及此类关键词，则**严禁**使用`approach_target`节点。
+9. **方向移动优先原则**：当指令仅要求“往/向/去往 + 东/西/南/北/前/后/左/右 + 飞/移动 + X米”（基于当前位置相对移动）且**未提及具体参照地点名词**（如“广场”、“大门”）时，**必须**使用`move_direction`节点，**严禁**计算坐标使用`fly_to_waypoint`。

-## 七、输出要求
+## 七、坐标计算规则（东北天坐标系 ENU）
+本系统统一使用东北天（ENU）坐标系：
+- **X轴**：正方向为**东** (East)，负方向为**西** (West)
+- **Y轴**：正方向为**北** (North)，负方向为**南** (South)
+- **Z轴**：正方向为**天** (Up)，负方向为**地** (Down)
+
+**仅当指令涉及前往“具体地点”（如广场、大门）的偏移位置时，才需计算绝对坐标并使用`fly_to_waypoint`：**
+假设参照点坐标为 $(x_0, y_0, z_0)$，偏移距离为 $d$：
+- **"去广场东边 $d$ 米"**：目标坐标 $(x_0 + d, y_0, z_0)$ （使用 `fly_to_waypoint`）
+- **"去广场西边 $d$ 米"**：目标坐标 $(x_0 - d, y_0, z_0)$ （使用 `fly_to_waypoint`）
+- **"去广场北边 $d$ 米"**：目标坐标 $(x_0, y_0 + d, z_0)$ （使用 `fly_to_waypoint`）
+- **"去广场南边 $d$ 米"**：目标坐标 $(x_0, y_0 - d, z_0)$ （使用 `fly_to_waypoint`）
+- **"往上/升高 $d$ 米"**：目标坐标 $(x_0, y_0, z_0 + d)$
+（注意：比如指令为“飞往东边100米”，请直接使用 `move_direction` 节点，无需计算坐标）
+
+**示例**：
+若"广场"坐标为 $(-17, 360, 3)$：
+- "去广场**东边**20米" -> 目标点 $(3, 360, 3)$
+- "去广场**南边**30米" -> 目标点 $(-17, 330, 3)$
+
+## 八、输出要求
 仅输出1个严格符合上述所有规则的JSON对象。
--- a/backend_service/src/py_tree_generator.py
+++ b/backend_service/src/py_tree_generator.py
@@ -282,6 +282,65 @@ def _generate_pytree_schema(allowed_actions: set, allowed_conditions: set) -> di
                        }
                    }
                }
+            },
+            # 飞行序列节点的参数验证
+            {
+                "if": {
+                    "properties": {
+                        "type": {"pattern": "^[Aa][Cc][Tt][Ii][Oo][Nn]$"},
+                        "name": {"const": "fly_sequence"}
+                    }
+                },
+                "then": {
+                    "properties": {
+                        "params": {
+                            "type": "object",
+                            "properties": {
+                                "waypoints": {
+                                    "type": "array",
+                                    "items": {
+                                        "type": "object",
+                                        "properties": {
+                                            "x": {"type": "number"},
+                                            "y": {"type": "number"},
+                                            "z": {"type": "number"}
+                                        },
+                                        "required": ["x", "y", "z"]
+                                    },
+                                    "minItems": 1
+                                },
+                                "coordinate_frame": {"type": "string", "enum": ["global", "local_enu"]},
+                                "speed": {"type": "number"}
+                            },
+                            "required": ["waypoints", "coordinate_frame"],
+                            "additionalProperties": False
+                        }
+                    }
+                }
+            },
+            # 抵近目标节点的参数验证
+            {
+                "if": {
+                    "properties": {
+                        "type": {"pattern": "^[Aa][Cc][Tt][Ii][Oo][Nn]$"},
+                        "name": {"const": "approach_target"}
+                    }
+                },
+                "then": {
+                    "properties": {
+                        "params": {
+                            "type": "object",
+                            "properties": {
+                                "target_class": {"type": "string"},
+                                "description": {"type": "string"},
+                                "stop_distance": {"type": "number"},
+                                "speed": {"type": "number"}
+                            },
+                            "required": ["target_class", "stop_distance"],
+                            "additionalProperties": False
+                        }
+                    }
+                }
            }
        ]
    }
@@ -602,6 +661,30 @@ class PyTreeGenerator:
            logging.error(f"从向量数据库检索时发生错误: {e}")
            return None

+    def _save_history(self, prompt: str, result_dict: dict):
+        """保存请求和响应历史记录"""
+        import datetime
+        try:
+            timestamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
+            # 确保history目录存在
+            history_dir = os.path.join(self.base_dir, '..', 'history')
+            os.makedirs(history_dir, exist_ok=True)
+            
+            history_file = os.path.join(history_dir, f"{timestamp}_plan.json")
+            
+            record = {
+                "timestamp": datetime.datetime.now().isoformat(),
+                "request": prompt,
+                "response": result_dict
+            }
+            
+            with open(history_file, 'w', encoding='utf-8') as f:
+                json.dump(record, f, ensure_ascii=False, indent=2)
+                
+            logging.info(f"💾 历史记录已保存: {history_file}")
+        except Exception as e:
+            logging.error(f"保存历史记录失败: {e}")
+
    async def generate(self, user_prompt: str) -> Dict[str, Any]:
        """
        Generates a py_tree.json structure based on the user's prompt.
@@ -798,6 +881,10 @@ class PyTreeGenerator:
                        logging.warning(f"保存推理链Markdown失败: {e}")
                    # 添加 final_prompt 到返回结果
                    pytree_dict['final_prompt'] = final_prompt
+                    
+                    # 保存历史记录
+                    self._save_history(user_prompt, pytree_dict)
+                    
                    return pytree_dict

                # 验证生成的复杂行为树
@@ -832,6 +919,10 @@ class PyTreeGenerator:
                        logging.warning(f"保存推理链Markdown失败: {e}")
                    # 添加 final_prompt 到返回结果
                    pytree_dict['final_prompt'] = final_prompt
+                    
+                    # 保存历史记录
+                    self._save_history(user_prompt, pytree_dict)
+                    
                    return pytree_dict
                else:
                    # 打印未通过验证的Pytree以便排查
--- a/start_all.sh
+++ b/start_all.sh
@@ -288,6 +288,21 @@ start_services() {
    print_info "启动FastAPI后端服务 (端口 ${API_PORT})..."
    cd "${PROJECT_ROOT}"
    
+    # 尝试找到 dot 命令 (Graphviz) 路径，以便后端生成图片
+    DOT_PATH=$(which dot || true)
+    DOT_DIR=""
+    if [ -n "$DOT_PATH" ]; then
+        DOT_DIR=$(dirname "$DOT_PATH")
+        print_info "找到 Graphviz dot 命令: $DOT_PATH"
+    else
+        print_warning "未找到 dot 命令，可视化图片生成可能会失败"
+        # 尝试默认的 miniconda 路径作为备选
+        if [ -f "/home/a/miniconda3/bin/dot" ]; then
+             DOT_DIR="/home/a/miniconda3/bin"
+             print_info "使用备选路径: $DOT_DIR"
+        fi
+    fi
+    
    # 激活venv虚拟环境并启动FastAPI服务
    # 使用bash -c来在新的shell中激活venv环境
    bash -c "
@@ -295,6 +310,12 @@ start_services() {
        if [ -f '${ros2_setup}' ]; then
            source '${ros2_setup}'
        fi
+        
+        # 确保 Graphviz 在 PATH 中
+        if [ -n '${DOT_DIR}' ]; then
+            export PATH=\"${DOT_DIR}:\$PATH\"
+        fi
+        
        # 直接使用虚拟环境中的Python启动
        cd '${PROJECT_ROOT}/backend_service' && \
        '${venv_path_expanded}/bin/python' -m uvicorn src.main:app --host 0.0.0.0 --port ${API_PORT}
--- a/start_all_vllm.sh
+++ b/start_all_vllm.sh
@@ -0,0 +1,477 @@
+#!/bin/bash
+
+# ==============================================================================
+# 无人机自然语言控制项目 - vLLM 一键启动脚本（新增，不修改 start_all.sh）
+# ==============================================================================
+# 功能：启动所有必需的服务（vLLM推理模型、llama-server embedding模型、FastAPI后端）
+# 用法：./start_all_vllm.sh [选项]
+# ==============================================================================
+
+set -e  # 遇到错误立即退出
+
+# 颜色定义
+RED='\033[0;31m'
+GREEN='\033[0;32m'
+YELLOW='\033[1;33m'
+BLUE='\033[0;34m'
+NC='\033[0m' # No Color
+
+# 默认配置（可通过环境变量覆盖）
+PROJECT_ROOT="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
+LLAMA_SERVER_DIR="${LLAMA_SERVER_DIR:-~/llama.cpp/build/bin}"
+INFERENCE_MODEL_DIR="${INFERENCE_MODEL_DIR:-/home/a/models/AWQ/Qwen3-4B-Instruct-2507}"
+VLLM_CONDA_ENV="${VLLM_CONDA_ENV:-VLLM}"
+VLLM_SPECULATIVE_CONFIG="${VLLM_SPECULATIVE_CONFIG:-}"
+VLLM_GPU_MEMORY_UTILIZATION="${VLLM_GPU_MEMORY_UTILIZATION:-0.6}"
+VLLM_SERVED_MODEL_NAME="${VLLM_SERVED_MODEL_NAME:-local-model}"
+EMBEDDING_MODEL="${EMBEDDING_MODEL:-~/models/gguf/Qwen3/Qwen3-Embedding-4B/Qwen3-Embedding-4B-Q5_K_M.gguf}"
+VENV_PATH="${VENV_PATH:-${PROJECT_ROOT}/backend_service/venv}"
+LOG_DIR="${LOG_DIR:-${PROJECT_ROOT}/logs}"
+PID_FILE="${LOG_DIR}/services_vllm.pid"
+
+# 端口配置
+INFERENCE_PORT="${INFERENCE_PORT:-8081}"
+EMBEDDING_PORT="${EMBEDDING_PORT:-8090}"
+API_PORT="${API_PORT:-8000}"
+
+# 创建日志目录
+mkdir -p "${LOG_DIR}"
+
+# ==============================================================================
+# 辅助函数
+# ==============================================================================
+
+print_info() {
+    echo -e "${BLUE}[INFO]${NC} $1"
+}
+
+print_success() {
+    echo -e "${GREEN}[SUCCESS]${NC} $1"
+}
+
+print_warning() {
+    echo -e "${YELLOW}[WARNING]${NC} $1"
+}
+
+print_error() {
+    echo -e "${RED}[ERROR]${NC} $1"
+}
+
+# 检查命令是否存在
+check_command() {
+    if ! command -v "$1" &> /dev/null; then
+        print_error "$1 命令未找到，请先安装"
+        return 1
+    fi
+    return 0
+}
+
+# 检查端口是否被占用
+check_port() {
+    local port=$1
+    if lsof -Pi :${port} -sTCP:LISTEN -t >/dev/null 2>&1 ; then
+        return 0  # 端口被占用
+    else
+        return 1  # 端口空闲
+    fi
+}
+
+# 等待服务就绪
+wait_for_service() {
+    local url=$1
+    local service_name=$2
+    local max_attempts=30
+    local attempt=0
+    
+    print_info "等待 ${service_name} 启动..."
+    while [ $attempt -lt $max_attempts ]; do
+        if curl -s "${url}" > /dev/null 2>&1; then
+            print_success "${service_name} 已就绪"
+            return 0
+        fi
+        attempt=$((attempt + 1))
+        sleep 1
+    done
+    
+    print_error "${service_name} 启动超时"
+    return 1
+}
+
+# 停止所有服务
+stop_services() {
+    print_info "正在停止所有服务..."
+    
+    if [ -f "${PID_FILE}" ]; then
+        while read -r pid; do
+            if ps -p "$pid" > /dev/null 2>&1; then
+                print_info "停止进程 PID: $pid"
+                kill "$pid" 2>/dev/null || true
+            fi
+        done < "${PID_FILE}"
+        rm -f "${PID_FILE}"
+    fi
+    
+    # 尝试通过端口停止服务
+    for port in ${INFERENCE_PORT} ${EMBEDDING_PORT} ${API_PORT}; do
+        if check_port ${port}; then
+            local pid
+            pid=$(lsof -ti:${port})
+            if [ -n "$pid" ]; then
+                print_info "停止占用端口 ${port} 的进程 (PID: $pid)"
+                kill $pid 2>/dev/null || true
+            fi
+        fi
+    done
+    
+    print_success "所有服务已停止"
+}
+
+# 清理函数（脚本退出时调用）
+cleanup() {
+    if [ "$?" -ne 0 ]; then
+        print_error "启动过程中发生错误，正在清理..."
+    fi
+    # 注意：这里不自动停止服务，让用户手动控制
+}
+
+trap cleanup EXIT
+
+# ==============================================================================
+# 主函数
+# ==============================================================================
+
+start_services() {
+    print_info "=========================================="
+    print_info "  无人机自然语言控制项目 - vLLM 服务启动"
+    print_info "=========================================="
+    echo ""
+    
+    # 检查必要的命令
+    print_info "检查必要的命令..."
+    check_command "python3" || exit 1
+    check_command "curl" || exit 1
+    check_command "lsof" || print_warning "lsof 未安装，将无法检查端口占用"
+    check_command "conda" || exit 1
+    echo ""
+    
+    # 检查端口占用
+    print_info "检查端口占用..."
+    if check_port ${INFERENCE_PORT}; then
+        print_warning "端口 ${INFERENCE_PORT} 已被占用，推理模型可能已在运行"
+    fi
+    if check_port ${EMBEDDING_PORT}; then
+        print_warning "端口 ${EMBEDDING_PORT} 已被占用，Embedding模型可能已在运行"
+    fi
+    if check_port ${API_PORT}; then
+        print_error "端口 ${API_PORT} 已被占用，请先停止占用该端口的服务"
+        exit 1
+    fi
+    echo ""
+    
+    # 检查llama-server（用于 embedding，展开路径中的 ~）
+    local llama_server_dir_expanded
+    llama_server_dir_expanded=$(eval echo "${LLAMA_SERVER_DIR}")
+    local llama_server="${llama_server_dir_expanded}/llama-server"
+    if [ ! -f "${llama_server}" ]; then
+        print_error "llama-server 未找到: ${llama_server}"
+        print_info "请设置 LLAMA_SERVER_DIR 环境变量指向正确的路径"
+        print_info "当前路径: ${LLAMA_SERVER_DIR}"
+        print_info "展开后路径: ${llama_server_dir_expanded}"
+        exit 1
+    fi
+    print_success "找到 llama-server: ${llama_server}"
+    echo ""
+    
+    # 检查模型路径
+    local inference_model_dir_expanded
+    inference_model_dir_expanded=$(eval echo "${INFERENCE_MODEL_DIR}")
+    local embedding_model_expanded
+    embedding_model_expanded=$(eval echo "${EMBEDDING_MODEL}")
+    
+    if [ ! -e "${inference_model_dir_expanded}" ]; then
+        print_error "推理模型目录未找到: ${inference_model_dir_expanded}"
+        print_info "请设置 INFERENCE_MODEL_DIR 环境变量指向正确的模型目录"
+        exit 1
+    fi
+    if [ ! -d "${inference_model_dir_expanded}" ]; then
+        print_warning "推理模型路径不是目录: ${inference_model_dir_expanded}"
+        print_warning "vLLM 通常需要传入模型目录（包含 config/tokenizer/权重等）"
+    fi
+    print_success "找到推理模型目录: ${inference_model_dir_expanded}"
+    
+    if [ ! -f "${embedding_model_expanded}" ]; then
+        print_error "Embedding模型文件未找到: ${embedding_model_expanded}"
+        print_info "请设置 EMBEDDING_MODEL 环境变量指向正确的模型路径"
+        exit 1
+    fi
+    print_success "找到Embedding模型: ${embedding_model_expanded}"
+    echo ""
+    
+    # 检查ROS2环境
+    local ros2_setup="${PROJECT_ROOT}/install/setup.bash"
+    if [ ! -f "${ros2_setup}" ]; then
+        print_warning "ROS2 setup文件未找到: ${ros2_setup}"
+        print_warning "如果项目已与ROS2解耦，可以忽略此警告"
+    else
+        print_success "找到ROS2 setup文件: ${ros2_setup}"
+    fi
+    echo ""
+    
+    # 检查venv虚拟环境
+    local venv_path_expanded
+    venv_path_expanded=$(eval echo "${VENV_PATH}")
+    print_info "检查venv虚拟环境: ${venv_path_expanded}"
+    if [ ! -d "${venv_path_expanded}" ]; then
+        print_error "venv虚拟环境目录不存在: ${venv_path_expanded}"
+        print_info "请先创建venv环境: python3 -m venv ${venv_path_expanded}"
+        print_info "然后安装依赖: ${venv_path_expanded}/bin/pip install -r backend_service/requirements.txt"
+        exit 1
+    fi
+    if [ ! -f "${venv_path_expanded}/bin/activate" ]; then
+        print_error "venv激活脚本不存在: ${venv_path_expanded}/bin/activate"
+        print_error "这看起来不是一个有效的venv环境"
+        exit 1
+    fi
+    print_success "venv虚拟环境存在: ${venv_path_expanded}"
+    echo ""
+    
+    # 初始化PID文件
+    > "${PID_FILE}"
+    
+    # ==========================================================================
+    # 启动推理模型服务（vLLM）
+    # ==========================================================================
+    print_info "启动推理模型服务(vLLM) (端口 ${INFERENCE_PORT})..."
+    bash -lc "
+        set -e
+        CONDA_BASE=\$(conda info --base)
+        if [ -z \"\${CONDA_BASE}\" ] || [ ! -f \"\${CONDA_BASE}/etc/profile.d/conda.sh\" ]; then
+            echo \"[ERROR] conda.sh 未找到：\${CONDA_BASE}/etc/profile.d/conda.sh\" 1>&2
+            exit 1
+        fi
+        source \"\${CONDA_BASE}/etc/profile.d/conda.sh\"
+        conda activate \"${VLLM_CONDA_ENV}\"
+        export VLLM_USE_V1=1
+        echo \"[DEBUG] conda_env=${VLLM_CONDA_ENV}\"
+        echo \"[DEBUG] CONDA_PREFIX=\${CONDA_PREFIX}\"
+        echo \"[DEBUG] which python: \$(which python)\"
+        echo \"[DEBUG] which vllm: \$(which vllm)\"
+        vllm --version || true
+        python -c \"import sys; print('[DEBUG] python:', sys.version)\" || true
+        python -c \"import torch; print('[DEBUG] torch:', torch.__version__, 'cuda:', torch.version.cuda, 'available:', torch.cuda.is_available())\" || true
+
+        SPEC_ARGS=()
+        if [ -n \"${VLLM_SPECULATIVE_CONFIG}\" ]; then
+            SPEC_ARGS+=(--speculative-config \"${VLLM_SPECULATIVE_CONFIG}\")
+        fi
+        exec vllm serve \"${inference_model_dir_expanded}\" \
+          --host=0.0.0.0 \
+          --port=${INFERENCE_PORT} \
+          --dtype=auto \
+          --max-num-seqs=1 \
+          --max-model-len=16384 \
+          \"\${SPEC_ARGS[@]}\" \
+          --served-model-name \"${VLLM_SERVED_MODEL_NAME}\" \
+          --trust-remote-code \
+          --gpu-memory-utilization=${VLLM_GPU_MEMORY_UTILIZATION} \
+          --uvicorn-log-level=debug \
+          --max-parallel-loading-workers 4
+    " > "${LOG_DIR}/vllm_inference_model.log" 2>&1 &
+    local inference_pid=$!
+    echo $inference_pid >> "${PID_FILE}"
+    print_success "推理模型服务(vLLM)已启动 (PID: $inference_pid)"
+    print_info "日志文件: ${LOG_DIR}/vllm_inference_model.log"
+    echo ""
+    
+    # ==========================================================================
+    # 启动Embedding模型服务（llama-server）
+    # ==========================================================================
+    print_info "启动Embedding模型服务 (端口 ${EMBEDDING_PORT})..."
+    cd "${llama_server_dir_expanded}"
+    nohup ./llama-server \
+        -m "${embedding_model_expanded}" \
+        --gpu-layers 36 \
+        --port ${EMBEDDING_PORT} \
+        --embeddings \
+        --pooling last \
+        --host 0.0.0.0 \
+        > "${LOG_DIR}/embedding_model.log" 2>&1 &
+    local embedding_pid=$!
+    echo $embedding_pid >> "${PID_FILE}"
+    print_success "Embedding模型服务已启动 (PID: $embedding_pid)"
+    print_info "日志文件: ${LOG_DIR}/embedding_model.log"
+    echo ""
+    
+    # ==========================================================================
+    # 等待模型服务就绪
+    # ==========================================================================
+    print_info "等待模型服务就绪..."
+    sleep 3  # 给服务一些启动时间
+    
+    # 等待推理模型服务（vLLM）
+    if ! wait_for_service "http://localhost:${INFERENCE_PORT}/health" "推理模型服务(vLLM)"; then
+        if ! wait_for_service "http://localhost:${INFERENCE_PORT}/v1/models" "推理模型服务(vLLM)"; then
+            print_warning "推理模型服务(vLLM)可能未完全就绪，但将继续启动"
+        fi
+    fi
+    
+    # 等待Embedding模型服务
+    if ! wait_for_service "http://localhost:${EMBEDDING_PORT}/health" "Embedding模型服务"; then
+        if ! wait_for_service "http://localhost:${EMBEDDING_PORT}/v1/models" "Embedding模型服务"; then
+            print_warning "Embedding模型服务可能未完全就绪，但将继续启动"
+        fi
+    fi
+    echo ""
+    
+    # ==========================================================================
+    # 启动FastAPI后端服务
+    # ==========================================================================
+    print_info "启动FastAPI后端服务 (端口 ${API_PORT})..."
+    cd "${PROJECT_ROOT}"
+    
+    # 尝试找到 dot 命令 (Graphviz) 路径，以便后端生成图片
+    DOT_PATH=$(which dot || true)
+    DOT_DIR=""
+    if [ -n "$DOT_PATH" ]; then
+        DOT_DIR=$(dirname "$DOT_PATH")
+        print_info "找到 Graphviz dot 命令: $DOT_PATH"
+    else
+        print_warning "未找到 dot 命令，可视化图片生成可能会失败"
+        # 尝试默认的 miniconda 路径作为备选
+        if [ -f "/home/a/miniconda3/bin/dot" ]; then
+             DOT_DIR="/home/a/miniconda3/bin"
+             print_info "使用备选路径: $DOT_DIR"
+        fi
+    fi
+
+    bash -c "
+        # 激活ROS2环境（如果存在）
+        if [ -f '${ros2_setup}' ]; then
+            source '${ros2_setup}'
+        fi
+        
+        # 确保 Graphviz 在 PATH 中
+        if [ -n '${DOT_DIR}' ]; then
+            export PATH=\"${DOT_DIR}:\$PATH\"
+        fi
+
+        # 让后端默认使用 vLLM 暴露的模型名，避免请求 local-model 导致 404
+        OPENAI_MODEL=\"\${OPENAI_MODEL:-${VLLM_SERVED_MODEL_NAME}}\" \
+        CLASSIFIER_MODEL=\"\${CLASSIFIER_MODEL:-${VLLM_SERVED_MODEL_NAME}}\" \
+        SIMPLE_MODEL=\"\${SIMPLE_MODEL:-${VLLM_SERVED_MODEL_NAME}}\" \
+        COMPLEX_MODEL=\"\${COMPLEX_MODEL:-${VLLM_SERVED_MODEL_NAME}}\" \
+        cd '${PROJECT_ROOT}/backend_service' && \
+        '${venv_path_expanded}/bin/python' -m uvicorn src.main:app --host 0.0.0.0 --port ${API_PORT}
+    " > "${LOG_DIR}/fastapi.log" 2>&1 &
+    local api_pid=$!
+    echo $api_pid >> "${PID_FILE}"
+    print_success "FastAPI服务已启动 (PID: $api_pid)"
+    print_info "日志文件: ${LOG_DIR}/fastapi.log"
+    echo ""
+    
+    # 等待FastAPI服务就绪
+    sleep 3
+    if wait_for_service "http://localhost:${API_PORT}/docs" "FastAPI服务"; then
+        print_success "所有服务已成功启动！"
+    else
+        print_warning "FastAPI服务可能未完全就绪，请检查日志: ${LOG_DIR}/fastapi.log"
+    fi
+    echo ""
+    
+    # 显示服务访问信息
+    print_info "=========================================="
+    print_info "  服务启动完成！"
+    print_info "=========================================="
+    print_info "推理模型API(vLLM): http://localhost:${INFERENCE_PORT}/v1"
+    print_info "Embedding模型API: http://localhost:${EMBEDDING_PORT}/v1"
+    print_info "FastAPI后端: http://localhost:${API_PORT}"
+    print_info "API文档: http://localhost:${API_PORT}/docs"
+    print_info ""
+    print_info "日志文件位置:"
+    print_info "  - 推理模型(vLLM): ${LOG_DIR}/vllm_inference_model.log"
+    print_info "  - Embedding模型: ${LOG_DIR}/embedding_model.log"
+    print_info "  - FastAPI服务: ${LOG_DIR}/fastapi.log"
+    print_info ""
+    print_info "按 Ctrl+C 停止所有服务"
+    print_info "=========================================="
+    echo ""
+    
+    # 设置信号处理，确保Ctrl+C时能清理
+    trap 'print_info "\n正在停止服务..."; stop_services; exit 0' INT TERM
+    
+    # 保持脚本运行
+    print_info "所有服务正在运行中，查看日志请使用:"
+    print_info "  tail -f ${LOG_DIR}/*.log"
+    echo ""
+    
+    wait
+}
+
+# ==============================================================================
+# 脚本入口
+# ==============================================================================
+
+case "${1:-start}" in
+    start)
+        start_services
+        ;;
+    stop)
+        stop_services
+        ;;
+    restart)
+        stop_services
+        sleep 2
+        start_services
+        ;;
+    status)
+        print_info "检查服务状态..."
+        if [ -f "${PID_FILE}" ]; then
+            print_info "已记录的服务进程:"
+            while read -r pid; do
+                if ps -p "$pid" > /dev/null 2>&1; then
+                    print_success "PID $pid: 运行中"
+                else
+                    print_warning "PID $pid: 已停止"
+                fi
+            done < "${PID_FILE}"
+        else
+            print_info "未找到PID文件，服务可能未启动"
+        fi
+        echo ""
+        print_info "端口占用情况:"
+        for port in ${INFERENCE_PORT} ${EMBEDDING_PORT} ${API_PORT}; do
+            if check_port ${port}; then
+                local pid
+                pid=$(lsof -ti:${port})
+                print_success "端口 ${port}: 被占用 (PID: $pid)"
+            else
+                print_warning "端口 ${port}: 空闲"
+            fi
+        done
+        ;;
+    *)
+        echo "用法: $0 {start|stop|restart|status}"
+        echo ""
+        echo "命令说明:"
+        echo "  start   - 启动所有服务（默认）"
+        echo "  stop    - 停止所有服务"
+        echo "  restart - 重启所有服务"
+        echo "  status  - 查看服务状态"
+        echo ""
+        echo "环境变量配置:"
+        echo "  LLAMA_SERVER_DIR     - llama-server所在目录 (默认: ~/llama.cpp/build/bin)"
+        echo "  INFERENCE_MODEL_DIR  - 推理模型目录(vLLM) (默认: /home/a/models/safetensors/Qwen3-4B)"
+        echo "  VLLM_CONDA_ENV       - conda环境名 (默认: vllm；如果你的是 VLLM，请设置为 VLLM)"
+        echo "  VLLM_SPECULATIVE_CONFIG - vLLM speculative JSON（可选；例如: {\"model\":\"/home/a/qwen3-4b-eagle3\",\"num_speculative_tokens\":5,\"method\":\"eagle3\"}）"
+        echo "  VLLM_GPU_MEMORY_UTILIZATION - vLLM 显存占用比例 (默认: 0.85)"
+        echo "  VLLM_SERVED_MODEL_NAME - vLLM 对外模型名 (默认: local-model；后端也会用它作为默认模型名)"
+        echo "  EMBEDDING_MODEL      - Embedding模型路径 (默认: ~/models/gguf/Qwen3/Qwen3-Embedding-4B/Qwen3-Embedding-4B-Q5_K_M.gguf)"
+        echo "  VENV_PATH            - venv虚拟环境路径 (默认: \${PROJECT_ROOT}/backend_service/venv)"
+        echo "  LOG_DIR              - 日志目录 (默认: \${PROJECT_ROOT}/logs)"
+        echo "  INFERENCE_PORT       - 推理端口 (默认: 8081)"
+        echo "  EMBEDDING_PORT       - embedding端口 (默认: 8090)"
+        echo "  API_PORT             - 后端端口 (默认: 8000)"
+        exit 1
+        ;;
+esac
+
--- a/tools/rag/knowledge_base/export_knowledge.ndjson
+++ b/tools/rag/knowledge_base/export_knowledge.ndjson
@@ -1,6 +0,0 @@
-{"text": "在地图上有一个名为 '跷跷板' 的地点或区域，它的leisure是'playground'，其中心位置坐标大约在 (x:15, y:-8.5, z:1.2)。"}
-{"text": "在地图上有一个名为 'A地' 的地点或区域，它的building是'commercial'，其中心位置坐标大约在 (x:10, y:-10, z:2)。"}
-{"text": "在地图上有一个名为 '学生宿舍' 的地点或区域，它的building是'dormitory'，其中心位置坐标大约在 (x:5, y:3, z:2)。"}
-{"text": "地点：'研究所正大门'。别名：'大门'、'入口'。坐标：(x:-23.8, y:292.8, z:14)。建议悬停高度：14米。适合任务：定点侦察、拍照。"}
-{"text": "地点：'研究所广场'。属性：开阔区域。坐标：(x:-24.0, y:241.8, z:14)。建议搜索半径：30米。适合任务：寻找人员、旋转搜索。"}
-{"text": "路线：'研究所外围巡逻'。关键航点序列：[(x:-24.0, y:241.8), (x:-107.8, y:289.8), (x:-106.5, y:241.3), (x:-23.80, y:292.80)]。高度：14米。适合环绕侦察任务。"}
--- a/tools/rag/knowledge_base/map.ndjson
+++ b/tools/rag/knowledge_base/map.ndjson
@@ -0,0 +1,8 @@
+{"text": "在地图上有一个名为 '跷跷板' 的地点或区域，它的leisure是'playground'，其中心位置坐标大约在东北天坐标系 (x:15, y:-8.5, z:1.2)。"}
+{"text": "在地图上有一个名为 'A地' 的地点或区域，它的building是'commercial'，其中心位置坐标大约在东北天坐标系 (x:10, y:-10, z:2)。"}
+{"text": "在地图上有一个名为 '学生宿舍' 的地点或区域，它的building是'dormitory'，其中心位置坐标大约在东北天坐标系 (x:5, y:3, z:2)。"}
+{"text": "地点：'研究所正大门'。别名：'大门'、'入口'。东北天坐标系坐标：(x:-23.8, y:292.8, z:14)。建议悬停高度：14米。适合任务：定点侦察、拍照。"}
+{"text": "地点：'广场'。属性：开阔区域。东北天坐标系坐标：(x:-17, y:360.0, z:3.0)。"}
+{"text": "对于查找搜索类任务，比如查找某个人或者东西，我们可以让无人机执行rotate_search动作节点，让无人机以自身为原点旋转，观察四周，确保无人机主动寻找目标。"}
+{"text": "大楼外围四个点东北天坐标系坐标：A(-24.00, 241.80),B(-108.50, 241.80),C(-108.50, 289.80),D(-24.00, 292.80)。"}
+{"text": "当指令中要求紧急返航到某地时，必须使用fly_to_waypoint节点，严禁使用return_emergency节点。"}
--- a/tools/rag/vector_store/23bb3f6e-b7de-4238-9726-2e27241977fd/data_level0.bin
+++ b/tools/rag/vector_store/23bb3f6e-b7de-4238-9726-2e27241977fd/data_level0.bin
--- a/tools/rag/vector_store/23bb3f6e-b7de-4238-9726-2e27241977fd/header.bin
+++ b/tools/rag/vector_store/23bb3f6e-b7de-4238-9726-2e27241977fd/header.bin
--- a/tools/rag/vector_store/23bb3f6e-b7de-4238-9726-2e27241977fd/length.bin
+++ b/tools/rag/vector_store/23bb3f6e-b7de-4238-9726-2e27241977fd/length.bin
--- a/tools/rag/vector_store/23bb3f6e-b7de-4238-9726-2e27241977fd/link_lists.bin
+++ b/tools/rag/vector_store/23bb3f6e-b7de-4238-9726-2e27241977fd/link_lists.bin
--- a/tools/rag/vector_store/chroma.sqlite3
+++ b/tools/rag/vector_store/chroma.sqlite3
--- a/tools/test_validate/api_test_log.txt
+++ b/tools/test_validate/api_test_log.txt
--- a/tools/test_validate/instructions.txt
+++ b/tools/test_validate/instructions.txt
@@ -1,14 +0,0 @@
-起飞
-起飞后移动到学生宿舍上方降落
-起飞后移动到学生宿舍上方查找蓝色的车
-起飞后移动到学生宿舍上方寻找蓝色的车
-起飞后移动到学生宿舍上方检测蓝色的车
-飞到学生宿舍上方查找蓝色的车
-飞到学生宿舍上方查找蓝色车辆并进行打击
-起飞后移动到学生宿舍上方搜索蓝色车辆，并进行打击
-起飞到学生宿舍上方搜索被困人员，并为被困人员投递救援物资
-飞到学生宿舍上方搜索方圆10米范围内的蓝色车辆
-飞到学生宿舍上方搜索半径为10米区域范围内的蓝色车辆
-起飞到学生宿舍搜索有没有被困人员，然后抛洒救援物资
-
-
--- a/tools/test_validate/instructions/scene1.txt
+++ b/tools/test_validate/instructions/scene1.txt
@@ -0,0 +1,2 @@
+无人机当前在地面，到广场查找穿黄色衣服的男子，找到后近距离拍照。
+无人机当前在空中，回到广场，对长发可疑男子进行拍照。
--- a/tools/test_validate/instructions/validate_instructions.txt
+++ b/tools/test_validate/instructions/validate_instructions.txt
@@ -1,5 +1,10 @@
-去研究所正大门，搜索扎辫子女子并拍照。
-查找戴帽子的女子，找到后近距离拍照。
-到研究所广场，对长发可疑男子进行拍照。
-到研究所广场，寻找黄色衣服男子，我确认后再对其拍照。
-立即返航。
+无人机当前在地面，到广场查找穿黄色衣服的男子，找到后近距离拍照。
+无人机当前在空中，回到广场，对戴帽子的人进行拍照。
+无人机当前在空中，去广场西边200米，对过往的公交车拍张照，然后返航。
+无人机当前在空中，到广场查找绿色公交车，看见了拍个照片。
+无人机当前在空中，搜索小汽车，搜索到了我确认后再决定要不要拍照。
+无人机当前在空中，往广场西边飞200米，持续监控5分钟，发现人就拍照告诉我，到时间可以返航。
+无人机当前在空中，到广场边上的施工区域内，发现有没带安全帽的飞近后拍照。
+无人机当前在空中，紧急回到广场，看见了红绿灯之后直接降落。
+无人机当前在空中，快速去往东边100米，有身穿黑色衣服，头戴帽子的男子在挟持他人，对其进行拍照。
+无人机当前在空中，离黑色衣服戴帽子的人太远了照片看不清，贴近到3米距离拍，拍完可以直接返航。
--- a/tools/test_validate/modules/pycache/json_visualizer.cpython-313.pyc
+++ b/tools/test_validate/modules/pycache/json_visualizer.cpython-313.pyc
--- a/tools/test_validate/modules/pycache/visualizer.cpython-313.pyc
+++ b/tools/test_validate/modules/pycache/visualizer.cpython-313.pyc
--- a/tools/test_validate/test_validity.py
+++ b/tools/test_validate/test_validity.py
@@ -154,8 +154,8 @@ def send_api_request(prompt, instruction_idx, run_number):
            def collect_nodes(current_node):
                if current_node.get('type') == 'action':
                    action_name = current_node.get('name', '')
-                    if action_name not in ['deliver_payload', 'emergency_return', 'fly_to_waypoint', 
-                                         'land', 'loiter', 'object_detect', 'preflight_checks', 
+                    if action_name not in ['deliver_payload', 'return', 'fly_to_waypoint', 
+                                         'land', 'loiter', 'object_detect', 'system_checks', 
                                         'search_pattern', 'strike_target', 'battle_damage_assessment', 'takeoff']:
                        invalid_actions.append(action_name)
                
@@ -178,8 +178,8 @@ def send_api_request(prompt, instruction_idx, run_number):
            elif is_simple_mode:
                # 简单模式：检查action名称是否有效
                action_name = root_node.get('name', '')
-                if action_name and action_name not in ['deliver_payload', 'emergency_return', 'fly_to_waypoint', 
-                                                       'land', 'loiter', 'object_detect', 'preflight_checks', 
+                if action_name and action_name not in ['deliver_payload', 'return', 'fly_to_waypoint', 
+                                                       'land', 'loiter', 'object_detect', 'system_checks', 
                                                       'search_pattern', 'strike_target', 'battle_damage_assessment', 'takeoff']:
                    invalid_actions.append(action_name)
            
--- a/tools/test_validate/validation/20260109140940/instructions_backup.txt
+++ b/tools/test_validate/validation/20260109140940/instructions_backup.txt
@@ -0,0 +1,10 @@
+无人机当前在地面，去研究所正大门，搜索扎辫子女子并拍照。
+无人机当前在空中，查找戴帽子的女子，找到后近距离拍照。
+无人机当前在地面，到研究所广场，对长发可疑男子进行拍照。
+无人机当前在空中，到研究所广场，寻找黄色衣服男子，我确认后再对其拍照。
+无人机当前在空中，立即返航。
+无人机当前在地面，去面前的大楼的三层/12米高,绕着外围侦察杂物堆积情况,如有发现拍照返回。
+无人机当前在地面，去面前的大楼的三层/12米高,绕着外围看有没有打开的窗户,发现则进行拍照。
+无人机当前在地面，飞到前面大楼3层/12米高,沿着外围查找打开的窗户,看到停下即可。
+无人机当前在空中，这层楼外围飞行过程中只要看到人,就拍照。
+无人机当前在空中，往上飞1层/3米高,接着绕这栋楼外围查有没有杂物堆积,看到了就拍照传回来。
--- a/tools/test_validate/validation/20260109140940/test_details.csv
+++ b/tools/test_validate/validation/20260109140940/test_details.csv
@@ -0,0 +1,11 @@
+instruction,run_id,success,latency,error
+无人机当前在地面，去研究所正大门，搜索扎辫子女子并拍照。,1,True,6.720000505447388,
+无人机当前在空中，查找戴帽子的女子，找到后近距离拍照。,1,True,4.619004487991333,
+无人机当前在地面，到研究所广场，对长发可疑男子进行拍照。,1,True,5.849743366241455,
+无人机当前在空中，到研究所广场，寻找黄色衣服男子，我确认后再对其拍照。,1,True,5.915772438049316,
+无人机当前在空中，立即返航。,1,True,0.7678096294403076,
+"无人机当前在地面，去面前的大楼的三层/12米高,绕着外围侦察杂物堆积情况,如有发现拍照返回。",1,True,26.149285554885864,
+"无人机当前在地面，去面前的大楼的三层/12米高,绕着外围看有没有打开的窗户,发现则进行拍照。",1,True,8.941612958908081,
+"无人机当前在地面，飞到前面大楼3层/12米高,沿着外围查找打开的窗户,看到停下即可。",1,True,5.791374444961548,
+"无人机当前在空中，这层楼外围飞行过程中只要看到人,就拍照。",1,True,5.722065687179565,
+"无人机当前在空中，往上飞1层/3米高,接着绕这栋楼外围查有没有杂物堆积,看到了就拍照传回来。",1,True,22.41797375679016,
--- a/tools/test_validate/validation/20260109140940/test_summary.csv
+++ b/tools/test_validate/validation/20260109140940/test_summary.csv
@@ -0,0 +1,11 @@
+Instruction,Total Runs,Success Runs,Success Rate,Avg Latency
+无人机当前在地面，去研究所正大门，搜索扎辫子女子并拍照。,1,1,100.0%,6.72s
+无人机当前在空中，查找戴帽子的女子，找到后近距离拍照。,1,1,100.0%,4.62s
+无人机当前在地面，到研究所广场，对长发可疑男子进行拍照。,1,1,100.0%,5.85s
+无人机当前在空中，到研究所广场，寻找黄色衣服男子，我确认后再对其拍照。,1,1,100.0%,5.92s
+无人机当前在空中，立即返航。,1,1,100.0%,0.77s
+"无人机当前在地面，去面前的大楼的三层/12米高,绕着外围侦察杂物堆积情况,如有发现拍照返回。",1,1,100.0%,26.15s
+"无人机当前在地面，去面前的大楼的三层/12米高,绕着外围看有没有打开的窗户,发现则进行拍照。",1,1,100.0%,8.94s
+"无人机当前在地面，飞到前面大楼3层/12米高,沿着外围查找打开的窗户,看到停下即可。",1,1,100.0%,5.79s
+"无人机当前在空中，这层楼外围飞行过程中只要看到人,就拍照。",1,1,100.0%,5.72s
+"无人机当前在空中，往上飞1层/3米高,接着绕这栋楼外围查有没有杂物堆积,看到了就拍照传回来。",1,1,100.0%,22.42s
--- a/tools/test_validate/validation/20260109140940/无人机当前在地面，到研究所广场，对长发可疑男子进行拍照。/1.json
+++ b/tools/test_validate/validation/20260109140940/无人机当前在地面，到研究所广场，对长发可疑男子进行拍照。/1.json
--- a/tools/test_validate/validation/20260109140940/无人机当前在地面，到研究所广场，对长发可疑男子进行拍照。/1.png
+++ b/tools/test_validate/validation/20260109140940/无人机当前在地面，到研究所广场，对长发可疑男子进行拍照。/1.png
--- a/tools/test_validate/validation/20260109140940/无人机当前在地面，去研究所正大门，搜索扎辫子女子并拍照。/1.json
+++ b/tools/test_validate/validation/20260109140940/无人机当前在地面，去研究所正大门，搜索扎辫子女子并拍照。/1.json
--- a/tools/test_validate/validation/20260109140940/无人机当前在地面，去研究所正大门，搜索扎辫子女子并拍照。/1.png
+++ b/tools/test_validate/validation/20260109140940/无人机当前在地面，去研究所正大门，搜索扎辫子女子并拍照。/1.png
--- a/tools/test_validate/validation/20260109140940/无人机当前在地面，去面前的大楼的三层_12米高,绕着外围侦察杂物堆积情况,如有发现拍照返回。/1.json
+++ b/tools/test_validate/validation/20260109140940/无人机当前在地面，去面前的大楼的三层_12米高,绕着外围侦察杂物堆积情况,如有发现拍照返回。/1.json
@@ -0,0 +1,3 @@
+{
+  "error": "在3次尝试后，仍未能生成一个有效的Pytree。"
+}
--- a/tools/test_validate/validation/20260109140940/无人机当前在地面，去面前的大楼的三层_12米高,绕着外围看有没有打开的窗户,发现则进行拍照。/1.json
+++ b/tools/test_validate/validation/20260109140940/无人机当前在地面，去面前的大楼的三层_12米高,绕着外围看有没有打开的窗户,发现则进行拍照。/1.json
--- a/tools/test_validate/validation/20260109140940/无人机当前在地面，去面前的大楼的三层_12米高,绕着外围看有没有打开的窗户,发现则进行拍照。/1.png
+++ b/tools/test_validate/validation/20260109140940/无人机当前在地面，去面前的大楼的三层_12米高,绕着外围看有没有打开的窗户,发现则进行拍照。/1.png
--- a/tools/test_validate/validation/20260109140940/无人机当前在地面，飞到前面大楼3层_12米高,沿着外围查找打开的窗户,看到停下即可。/1.json
+++ b/tools/test_validate/validation/20260109140940/无人机当前在地面，飞到前面大楼3层_12米高,沿着外围查找打开的窗户,看到停下即可。/1.json
--- a/tools/test_validate/validation/20260109140940/无人机当前在地面，飞到前面大楼3层_12米高,沿着外围查找打开的窗户,看到停下即可。/1.png
+++ b/tools/test_validate/validation/20260109140940/无人机当前在地面，飞到前面大楼3层_12米高,沿着外围查找打开的窗户,看到停下即可。/1.png
--- a/tools/test_validate/validation/20260109140940/无人机当前在空中，到研究所广场，寻找黄色衣服男子，我确认后再对其拍照。/1.json
+++ b/tools/test_validate/validation/20260109140940/无人机当前在空中，到研究所广场，寻找黄色衣服男子，我确认后再对其拍照。/1.json
--- a/tools/test_validate/validation/20260109140940/无人机当前在空中，到研究所广场，寻找黄色衣服男子，我确认后再对其拍照。/1.png
+++ b/tools/test_validate/validation/20260109140940/无人机当前在空中，到研究所广场，寻找黄色衣服男子，我确认后再对其拍照。/1.png
--- a/tools/test_validate/validation/20260109140940/无人机当前在空中，往上飞1层_3米高,接着绕这栋楼外围查有没有杂物堆积,看到了就拍照传回来。/1.json
+++ b/tools/test_validate/validation/20260109140940/无人机当前在空中，往上飞1层_3米高,接着绕这栋楼外围查有没有杂物堆积,看到了就拍照传回来。/1.json
@@ -0,0 +1,3 @@
+{
+  "error": "在3次尝试后，仍未能生成一个有效的Pytree。"
+}
--- a/tools/test_validate/validation/20260109140940/无人机当前在空中，查找戴帽子的女子，找到后近距离拍照。/1.json
+++ b/tools/test_validate/validation/20260109140940/无人机当前在空中，查找戴帽子的女子，找到后近距离拍照。/1.json
--- a/tools/test_validate/validation/20260109140940/无人机当前在空中，查找戴帽子的女子，找到后近距离拍照。/1.png
+++ b/tools/test_validate/validation/20260109140940/无人机当前在空中，查找戴帽子的女子，找到后近距离拍照。/1.png
--- a/tools/test_validate/validation/20260109140940/无人机当前在空中，立即返航。/1.json
+++ b/tools/test_validate/validation/20260109140940/无人机当前在空中，立即返航。/1.json
--- a/tools/test_validate/validation/20260109140940/无人机当前在空中，立即返航。/1.png
+++ b/tools/test_validate/validation/20260109140940/无人机当前在空中，立即返航。/1.png
--- a/tools/test_validate/validation/20260109140940/无人机当前在空中，这层楼外围飞行过程中只要看到人,就拍照。/1.json
+++ b/tools/test_validate/validation/20260109140940/无人机当前在空中，这层楼外围飞行过程中只要看到人,就拍照。/1.json
--- a/tools/test_validate/validation/20260109140940/无人机当前在空中，这层楼外围飞行过程中只要看到人,就拍照。/1.png
+++ b/tools/test_validate/validation/20260109140940/无人机当前在空中，这层楼外围飞行过程中只要看到人,就拍照。/1.png
--- a/tools/test_validate/validation/20260113153508/instructions_backup.txt
+++ b/tools/test_validate/validation/20260113153508/instructions_backup.txt
@@ -0,0 +1,2 @@
+无人机当前在地面，到广场查找穿黄色衣服的男子，找到后近距离拍照。
+无人机当前在空中，回到广场，对长发可疑男子进行拍照。
--- a/tools/test_validate/validation/20260113153508/test_details.csv
+++ b/tools/test_validate/validation/20260113153508/test_details.csv
@@ -0,0 +1,3 @@
+instruction,run_id,success,latency,error
+无人机当前在地面，到广场查找穿黄色衣服的男子，找到后近距离拍照。,1,True,6.9019341468811035,
+无人机当前在空中，回到广场，对长发可疑男子进行拍照。,1,True,5.214093923568726,
--- a/tools/test_validate/validation/20260113153508/test_summary.csv
+++ b/tools/test_validate/validation/20260113153508/test_summary.csv
@@ -0,0 +1,3 @@
+Instruction,Total Runs,Success Runs,Success Rate,Avg Latency
+无人机当前在地面，到广场查找穿黄色衣服的男子，找到后近距离拍照。,1,1,100.0%,6.90s
+无人机当前在空中，回到广场，对长发可疑男子进行拍照。,1,1,100.0%,5.21s
--- a/tools/test_validate/validation/20260113153508/无人机当前在地面，到广场查找穿黄色衣服的男子，找到后近距离拍照。/1.json
+++ b/tools/test_validate/validation/20260113153508/无人机当前在地面，到广场查找穿黄色衣服的男子，找到后近距离拍照。/1.json
--- a/tools/test_validate/validation/20260113153508/无人机当前在地面，到广场查找穿黄色衣服的男子，找到后近距离拍照。/1.png
+++ b/tools/test_validate/validation/20260113153508/无人机当前在地面，到广场查找穿黄色衣服的男子，找到后近距离拍照。/1.png
--- a/tools/test_validate/validation/20260113153508/无人机当前在空中，回到广场，对长发可疑男子进行拍照。/1.json
+++ b/tools/test_validate/validation/20260113153508/无人机当前在空中，回到广场，对长发可疑男子进行拍照。/1.json
--- a/tools/test_validate/validation/20260113153508/无人机当前在空中，回到广场，对长发可疑男子进行拍照。/1.png
+++ b/tools/test_validate/validation/20260113153508/无人机当前在空中，回到广场，对长发可疑男子进行拍照。/1.png
--- a/tools/test_validate/validation/20260113153656/instructions_backup.txt
+++ b/tools/test_validate/validation/20260113153656/instructions_backup.txt
@@ -0,0 +1,2 @@
+无人机当前在地面，到广场查找穿黄色衣服的男子，找到后近距离拍照。
+无人机当前在空中，回到广场，对长发可疑男子进行拍照。
--- a/tools/test_validate/validation/20260113153656/test_details.csv
+++ b/tools/test_validate/validation/20260113153656/test_details.csv
@@ -0,0 +1,3 @@
+instruction,run_id,success,latency,error
+无人机当前在地面，到广场查找穿黄色衣服的男子，找到后近距离拍照。,1,True,7.12662148475647,
+无人机当前在空中，回到广场，对长发可疑男子进行拍照。,1,True,5.365821123123169,
--- a/tools/test_validate/validation/20260113153656/test_summary.csv
+++ b/tools/test_validate/validation/20260113153656/test_summary.csv
@@ -0,0 +1,3 @@
+Instruction,Total Runs,Success Runs,Success Rate,Avg Latency
+无人机当前在地面，到广场查找穿黄色衣服的男子，找到后近距离拍照。,1,1,100.0%,7.13s
+无人机当前在空中，回到广场，对长发可疑男子进行拍照。,1,1,100.0%,5.37s
--- a/tools/test_validate/validation/20260113153656/无人机当前在地面，到广场查找穿黄色衣服的男子，找到后近距离拍照。/1.json
+++ b/tools/test_validate/validation/20260113153656/无人机当前在地面，到广场查找穿黄色衣服的男子，找到后近距离拍照。/1.json
--- a/tools/test_validate/validation/20260113153656/无人机当前在地面，到广场查找穿黄色衣服的男子，找到后近距离拍照。/1.png
+++ b/tools/test_validate/validation/20260113153656/无人机当前在地面，到广场查找穿黄色衣服的男子，找到后近距离拍照。/1.png
--- a/tools/test_validate/validation/20260113153656/无人机当前在空中，回到广场，对长发可疑男子进行拍照。/1.json
+++ b/tools/test_validate/validation/20260113153656/无人机当前在空中，回到广场，对长发可疑男子进行拍照。/1.json
--- a/tools/test_validate/validation/20260113153656/无人机当前在空中，回到广场，对长发可疑男子进行拍照。/1.png
+++ b/tools/test_validate/validation/20260113153656/无人机当前在空中，回到广场，对长发可疑男子进行拍照。/1.png
--- a/tools/test_validate/validation/20260113153914/instructions_backup.txt
+++ b/tools/test_validate/validation/20260113153914/instructions_backup.txt
@@ -0,0 +1,2 @@
+无人机当前在地面，到广场查找穿黄色衣服的男子，找到后近距离拍照。
+无人机当前在空中，回到广场，对长发可疑男子进行拍照。
--- a/tools/test_validate/validation/20260113153914/test_details.csv
+++ b/tools/test_validate/validation/20260113153914/test_details.csv
@@ -0,0 +1,3 @@
+instruction,run_id,success,latency,error
+无人机当前在地面，到广场查找穿黄色衣服的男子，找到后近距离拍照。,1,True,7.271864414215088,
+无人机当前在空中，回到广场，对长发可疑男子进行拍照。,1,True,4.198384046554565,
--- a/tools/test_validate/validation/20260113153914/test_summary.csv
+++ b/tools/test_validate/validation/20260113153914/test_summary.csv
@@ -0,0 +1,3 @@
+Instruction,Total Runs,Success Runs,Success Rate,Avg Latency
+无人机当前在地面，到广场查找穿黄色衣服的男子，找到后近距离拍照。,1,1,100.0%,7.27s
+无人机当前在空中，回到广场，对长发可疑男子进行拍照。,1,1,100.0%,4.20s
--- a/tools/test_validate/validation/20260113153914/无人机当前在地面，到广场查找穿黄色衣服的男子，找到后近距离拍照。/1.json
+++ b/tools/test_validate/validation/20260113153914/无人机当前在地面，到广场查找穿黄色衣服的男子，找到后近距离拍照。/1.json
--- a/tools/test_validate/validation/20260113153914/无人机当前在地面，到广场查找穿黄色衣服的男子，找到后近距离拍照。/1.png
+++ b/tools/test_validate/validation/20260113153914/无人机当前在地面，到广场查找穿黄色衣服的男子，找到后近距离拍照。/1.png
--- a/tools/test_validate/validation/20260113153914/无人机当前在空中，回到广场，对长发可疑男子进行拍照。/1.json
+++ b/tools/test_validate/validation/20260113153914/无人机当前在空中，回到广场，对长发可疑男子进行拍照。/1.json
--- a/tools/test_validate/validation/20260113153914/无人机当前在空中，回到广场，对长发可疑男子进行拍照。/1.png
+++ b/tools/test_validate/validation/20260113153914/无人机当前在空中，回到广场，对长发可疑男子进行拍照。/1.png
--- a/tools/test_validate/validation/20260113153958/instructions_backup.txt
+++ b/tools/test_validate/validation/20260113153958/instructions_backup.txt
@@ -0,0 +1,2 @@
+无人机当前在地面，到广场查找穿黄色衣服的男子，找到后近距离拍照。
+无人机当前在空中，回到广场，对长发可疑男子进行拍照。
--- a/tools/test_validate/validation/20260113153958/test_details.csv
+++ b/tools/test_validate/validation/20260113153958/test_details.csv
@@ -0,0 +1,3 @@
+instruction,run_id,success,latency,error
+无人机当前在地面，到广场查找穿黄色衣服的男子，找到后近距离拍照。,1,True,6.254483222961426,
+无人机当前在空中，回到广场，对长发可疑男子进行拍照。,1,True,4.200452089309692,
--- a/tools/test_validate/validation/20260113153958/test_summary.csv
+++ b/tools/test_validate/validation/20260113153958/test_summary.csv
@@ -0,0 +1,3 @@
+Instruction,Total Runs,Success Runs,Success Rate,Avg Latency
+无人机当前在地面，到广场查找穿黄色衣服的男子，找到后近距离拍照。,1,1,100.0%,6.25s
+无人机当前在空中，回到广场，对长发可疑男子进行拍照。,1,1,100.0%,4.20s
--- a/tools/test_validate/validation/20260113153958/无人机当前在地面，到广场查找穿黄色衣服的男子，找到后近距离拍照。/1.json
+++ b/tools/test_validate/validation/20260113153958/无人机当前在地面，到广场查找穿黄色衣服的男子，找到后近距离拍照。/1.json
--- a/tools/test_validate/validation/20260113153958/无人机当前在地面，到广场查找穿黄色衣服的男子，找到后近距离拍照。/1.png
+++ b/tools/test_validate/validation/20260113153958/无人机当前在地面，到广场查找穿黄色衣服的男子，找到后近距离拍照。/1.png
--- a/tools/test_validate/validation/20260113153958/无人机当前在空中，回到广场，对长发可疑男子进行拍照。/1.json
+++ b/tools/test_validate/validation/20260113153958/无人机当前在空中，回到广场，对长发可疑男子进行拍照。/1.json
--- a/tools/test_validate/validation/20260113153958/无人机当前在空中，回到广场，对长发可疑男子进行拍照。/1.png
+++ b/tools/test_validate/validation/20260113153958/无人机当前在空中，回到广场，对长发可疑男子进行拍照。/1.png
--- a/tools/test_validate/validation/20260115184420/instructions_backup.txt
+++ b/tools/test_validate/validation/20260115184420/instructions_backup.txt
@@ -0,0 +1,10 @@
+无人机当前在地面，到广场查找穿黄色衣服的男子,找到后近距离拍照。
+无人机当前在空中，回到广场,对戴帽子的人进行拍照。
+无人机当前在空中，去广场西边200米,对过往的公交车拍张照,然后返航。
+无人机当前在空中，到广场查找绿色公交车,看见了拍个照片。
+无人机当前在空中，搜索小汽车,搜索到了我确认后再决定要不要拍照。
+无人机当前在空中，往东边飞50米,停个20s就好返航了。
+无人机当前在空中，到广场边上的施工区域内,发现有没带安全帽的飞近后拍照。
+无人机当前在空中，紧急回到广场,看见了红绿灯之后直接降落。
+无人机当前在空中，快速去往东边100米,有身穿黑色衣服,头戴帽子的男子在挟持他人,对其进行拍照。
+无人机当前在空中，离黑色衣服戴帽子的人太远了照片看不清,贴近到3米距离拍,拍完司以直接返航。
--- a/tools/test_validate/validation/20260115184420/test_details.csv
+++ b/tools/test_validate/validation/20260115184420/test_details.csv
@@ -0,0 +1,11 @@
+instruction,run_id,success,latency,error
+"无人机当前在地面，到广场查找穿黄色衣服的男子,找到后近距离拍照。",1,True,6.352114677429199,
+"无人机当前在空中，回到广场,对戴帽子的人进行拍照。",1,True,5.022204637527466,
+"无人机当前在空中，去广场西边200米,对过往的公交车拍张照,然后返航。",1,True,3.8677239418029785,
+"无人机当前在空中，到广场查找绿色公交车,看见了拍个照片。",1,True,4.64957594871521,
+"无人机当前在空中，搜索小汽车,搜索到了我确认后再决定要不要拍照。",1,True,3.5267481803894043,
+"无人机当前在空中，往东边飞50米,停个20s就好返航了。",1,True,0.8441617488861084,
+"无人机当前在空中，到广场边上的施工区域内,发现有没带安全帽的飞近后拍照。",1,True,4.096853733062744,
+"无人机当前在空中，紧急回到广场,看见了红绿灯之后直接降落。",1,True,2.7230677604675293,
+"无人机当前在空中，快速去往东边100米,有身穿黑色衣服,头戴帽子的男子在挟持他人,对其进行拍照。",1,True,5.245810031890869,
+"无人机当前在空中，离黑色衣服戴帽子的人太远了照片看不清,贴近到3米距离拍,拍完司以直接返航。",1,True,2.8097290992736816,
--- a/tools/test_validate/validation/20260115184420/test_summary.csv
+++ b/tools/test_validate/validation/20260115184420/test_summary.csv
@@ -0,0 +1,11 @@
+Instruction,Total Runs,Success Runs,Success Rate,Avg Latency
+"无人机当前在地面，到广场查找穿黄色衣服的男子,找到后近距离拍照。",1,1,100.0%,6.35s
+"无人机当前在空中，回到广场,对戴帽子的人进行拍照。",1,1,100.0%,5.02s
+"无人机当前在空中，去广场西边200米,对过往的公交车拍张照,然后返航。",1,1,100.0%,3.87s
+"无人机当前在空中，到广场查找绿色公交车,看见了拍个照片。",1,1,100.0%,4.65s
+"无人机当前在空中，搜索小汽车,搜索到了我确认后再决定要不要拍照。",1,1,100.0%,3.53s
+"无人机当前在空中，往东边飞50米,停个20s就好返航了。",1,1,100.0%,0.84s
+"无人机当前在空中，到广场边上的施工区域内,发现有没带安全帽的飞近后拍照。",1,1,100.0%,4.10s
+"无人机当前在空中，紧急回到广场,看见了红绿灯之后直接降落。",1,1,100.0%,2.72s
+"无人机当前在空中，快速去往东边100米,有身穿黑色衣服,头戴帽子的男子在挟持他人,对其进行拍照。",1,1,100.0%,5.25s
+"无人机当前在空中，离黑色衣服戴帽子的人太远了照片看不清,贴近到3米距离拍,拍完司以直接返航。",1,1,100.0%,2.81s
--- a/tools/test_validate/validation/20260115184420/无人机当前在地面，到广场查找穿黄色衣服的男子,找到后近距离拍照。/1.json
+++ b/tools/test_validate/validation/20260115184420/无人机当前在地面，到广场查找穿黄色衣服的男子,找到后近距离拍照。/1.json
--- a/tools/test_validate/validation/20260115184420/无人机当前在地面，到广场查找穿黄色衣服的男子,找到后近距离拍照。/1.png
+++ b/tools/test_validate/validation/20260115184420/无人机当前在地面，到广场查找穿黄色衣服的男子,找到后近距离拍照。/1.png
--- a/tools/test_validate/validation/20260115184420/无人机当前在空中，到广场查找绿色公交车,看见了拍个照片。/1.json
+++ b/tools/test_validate/validation/20260115184420/无人机当前在空中，到广场查找绿色公交车,看见了拍个照片。/1.json
--- a/tools/test_validate/validation/20260115184420/无人机当前在空中，到广场查找绿色公交车,看见了拍个照片。/1.png
+++ b/tools/test_validate/validation/20260115184420/无人机当前在空中，到广场查找绿色公交车,看见了拍个照片。/1.png
--- a/tools/test_validate/validation/20260115184420/无人机当前在空中，到广场边上的施工区域内,发现有没带安全帽的飞近后拍照。/1.json
+++ b/tools/test_validate/validation/20260115184420/无人机当前在空中，到广场边上的施工区域内,发现有没带安全帽的飞近后拍照。/1.json
--- a/tools/test_validate/validation/20260115184420/无人机当前在空中，到广场边上的施工区域内,发现有没带安全帽的飞近后拍照。/1.png
+++ b/tools/test_validate/validation/20260115184420/无人机当前在空中，到广场边上的施工区域内,发现有没带安全帽的飞近后拍照。/1.png
--- a/tools/test_validate/validation/20260115184420/无人机当前在空中，去广场西边200米,对过往的公交车拍张照,然后返航。/1.json
+++ b/tools/test_validate/validation/20260115184420/无人机当前在空中，去广场西边200米,对过往的公交车拍张照,然后返航。/1.json
--- a/tools/test_validate/validation/20260115184420/无人机当前在空中，去广场西边200米,对过往的公交车拍张照,然后返航。/1.png
+++ b/tools/test_validate/validation/20260115184420/无人机当前在空中，去广场西边200米,对过往的公交车拍张照,然后返航。/1.png
--- a/tools/test_validate/validation/20260115184420/无人机当前在空中，回到广场,对戴帽子的人进行拍照。/1.json
+++ b/tools/test_validate/validation/20260115184420/无人机当前在空中，回到广场,对戴帽子的人进行拍照。/1.json
--- a/tools/test_validate/validation/20260115184420/无人机当前在空中，回到广场,对戴帽子的人进行拍照。/1.png
+++ b/tools/test_validate/validation/20260115184420/无人机当前在空中，回到广场,对戴帽子的人进行拍照。/1.png
--- a/tools/test_validate/validation/20260115184420/无人机当前在空中，往东边飞50米,停个20s就好返航了。/1.json
+++ b/tools/test_validate/validation/20260115184420/无人机当前在空中，往东边飞50米,停个20s就好返航了。/1.json
--- a/tools/test_validate/validation/20260115184420/无人机当前在空中，往东边飞50米,停个20s就好返航了。/1.png
+++ b/tools/test_validate/validation/20260115184420/无人机当前在空中，往东边飞50米,停个20s就好返航了。/1.png
--- a/tools/test_validate/validation/20260115184420/无人机当前在空中，快速去往东边100米,有身穿黑色衣服,头戴帽子的男子在挟持他人,对其进行拍照。/1.json
+++ b/tools/test_validate/validation/20260115184420/无人机当前在空中，快速去往东边100米,有身穿黑色衣服,头戴帽子的男子在挟持他人,对其进行拍照。/1.json
--- a/tools/test_validate/validation/20260115184420/无人机当前在空中，快速去往东边100米,有身穿黑色衣服,头戴帽子的男子在挟持他人,对其进行拍照。/1.png
+++ b/tools/test_validate/validation/20260115184420/无人机当前在空中，快速去往东边100米,有身穿黑色衣服,头戴帽子的男子在挟持他人,对其进行拍照。/1.png
--- a/tools/test_validate/validation/20260115184420/无人机当前在空中，搜索小汽车,搜索到了我确认后再决定要不要拍照。/1.json
+++ b/tools/test_validate/validation/20260115184420/无人机当前在空中，搜索小汽车,搜索到了我确认后再决定要不要拍照。/1.json
--- a/tools/test_validate/validation/20260115184420/无人机当前在空中，搜索小汽车,搜索到了我确认后再决定要不要拍照。/1.png
+++ b/tools/test_validate/validation/20260115184420/无人机当前在空中，搜索小汽车,搜索到了我确认后再决定要不要拍照。/1.png
--- a/tools/test_validate/validation/20260115184420/无人机当前在空中，离黑色衣服戴帽子的人太远了照片看不清,贴近到3米距离拍,拍完司以直接返航。/1.json
+++ b/tools/test_validate/validation/20260115184420/无人机当前在空中，离黑色衣服戴帽子的人太远了照片看不清,贴近到3米距离拍,拍完司以直接返航。/1.json
--- a/tools/test_validate/validation/20260115184420/无人机当前在空中，离黑色衣服戴帽子的人太远了照片看不清,贴近到3米距离拍,拍完司以直接返航。/1.png
+++ b/tools/test_validate/validation/20260115184420/无人机当前在空中，离黑色衣服戴帽子的人太远了照片看不清,贴近到3米距离拍,拍完司以直接返航。/1.png
--- a/tools/test_validate/validation/20260115184420/无人机当前在空中，紧急回到广场,看见了红绿灯之后直接降落。/1.json
+++ b/tools/test_validate/validation/20260115184420/无人机当前在空中，紧急回到广场,看见了红绿灯之后直接降落。/1.json
--- a/tools/test_validate/validation/20260115184420/无人机当前在空中，紧急回到广场,看见了红绿灯之后直接降落。/1.png
+++ b/tools/test_validate/validation/20260115184420/无人机当前在空中，紧急回到广场,看见了红绿灯之后直接降落。/1.png
--- a/tools/test_validate/validation/20260116095521/instructions_backup.txt
+++ b/tools/test_validate/validation/20260116095521/instructions_backup.txt
@@ -0,0 +1,10 @@
+无人机当前在地面，到广场查找穿黄色衣服的男子,找到后近距离拍照。
+无人机当前在空中，回到广场,对戴帽子的人进行拍照。
+无人机当前在空中，去广场西边200米,对过往的公交车拍张照,然后返航。
+无人机当前在空中，到广场查找绿色公交车,看见了拍个照片。
+无人机当前在空中，搜索小汽车,搜索到了我确认后再决定要不要拍照。
+无人机当前在空中，往东边飞50米,停个20s就好返航了。
+无人机当前在空中，到广场边上的施工区域内,发现有没带安全帽的飞近后拍照。
+无人机当前在空中，紧急回到广场,看见了红绿灯之后直接降落。
+无人机当前在空中，快速去往东边100米,有身穿黑色衣服,头戴帽子的男子在挟持他人,对其进行拍照。
+无人机当前在空中，离黑色衣服戴帽子的人太远了照片看不清,贴近到3米距离拍,拍完司以直接返航。
--- a/tools/test_validate/validation/20260116095521/无人机当前在地面，到广场查找穿黄色衣服的男子,找到后近距离拍照。/1.json
+++ b/tools/test_validate/validation/20260116095521/无人机当前在地面，到广场查找穿黄色衣服的男子,找到后近距离拍照。/1.json
--- a/tools/test_validate/validation/20260116095521/无人机当前在地面，到广场查找穿黄色衣服的男子,找到后近距离拍照。/1.png
+++ b/tools/test_validate/validation/20260116095521/无人机当前在地面，到广场查找穿黄色衣服的男子,找到后近距离拍照。/1.png
--- a/tools/test_validate/validation/20260116095521/无人机当前在地面，到广场查找穿黄色衣服的男子,找到后近距离拍照。/10.json
+++ b/tools/test_validate/validation/20260116095521/无人机当前在地面，到广场查找穿黄色衣服的男子,找到后近距离拍照。/10.json
--- a/tools/test_validate/validation/20260116095521/无人机当前在地面，到广场查找穿黄色衣服的男子,找到后近距离拍照。/10.png
+++ b/tools/test_validate/validation/20260116095521/无人机当前在地面，到广场查找穿黄色衣服的男子,找到后近距离拍照。/10.png
--- a/tools/test_validate/validation/20260116095521/无人机当前在地面，到广场查找穿黄色衣服的男子,找到后近距离拍照。/11.json
+++ b/tools/test_validate/validation/20260116095521/无人机当前在地面，到广场查找穿黄色衣服的男子,找到后近距离拍照。/11.json
--- a/tools/test_validate/validation/20260116095521/无人机当前在地面，到广场查找穿黄色衣服的男子,找到后近距离拍照。/11.png
+++ b/tools/test_validate/validation/20260116095521/无人机当前在地面，到广场查找穿黄色衣服的男子,找到后近距离拍照。/11.png
--- a/Show More
+++ b/Show More