fix: 修复路径执行精度问题
- 修改可视化方法显示真实的插值轨迹 - 修复RRT*算法路径终点精度，确保以精确目标结束 - 删除路径执行器的垃圾提前返回逻辑 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
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@ -23,6 +23,10 @@ from src.planning.path_executor import PathExecutor
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# GUI设置
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DEFAULT_WINDOW_SIZE = "1200x800"
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# 按钮文本常量
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EXECUTE_BUTTON_TEXT = "执行三阶段任务"
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EXECUTE_BUTTON_BG = "#00BCD4"
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# 相机默认设置
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DEFAULT_CAMERA_DISTANCE = 4.0
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DEFAULT_CAMERA_YAW = 45
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@ -50,7 +54,6 @@ class MainWindow:
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self.collision_checker = None
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self.path_optimizer = None
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self.path_executor = None
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self.planned_path = None
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# Simulation state
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self.simulation_running = False
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@ -131,19 +134,13 @@ class MainWindow:
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# Path planning section
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planning_frame = tk.LabelFrame(left_panel, text="Path Planning", padx=10, pady=10)
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planning_frame.pack(fill=tk.X, pady=(0, 10))
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self.plan_btn = tk.Button(planning_frame, text="Plan Path (AI RRT*)",
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command=self.plan_path,
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bg="#00BCD4", fg="white", padx=10, pady=5)
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self.plan_btn.pack(fill=tk.X)
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self.execute_btn = tk.Button(planning_frame, text="Execute Path",
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command=self.execute_path,
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bg="#8BC34A", fg="white", padx=10, pady=5,
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state=tk.DISABLED)
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self.execute_btn.pack(fill=tk.X, pady=(5, 0))
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tk.Label(planning_frame, text="Plan and execute path through hole",
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self.execute_btn = tk.Button(planning_frame, text=EXECUTE_BUTTON_TEXT,
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command=self.execute_three_stages,
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bg=EXECUTE_BUTTON_BG, fg="white", padx=10, pady=5)
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self.execute_btn.pack(fill=tk.X)
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tk.Label(planning_frame, text="Execute three-stage path: Current→Object→A→B",
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font=("Arial", 9)).pack(pady=(5, 0))
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# Status section
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@ -364,10 +361,6 @@ class MainWindow:
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p.removeBody(marker_id)
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self.point_markers = []
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# Reset planned path
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self.planned_path = None
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self.execute_btn.config(state=tk.DISABLED)
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# Reset camera
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self._reset_camera_view()
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@ -471,284 +464,256 @@ class MainWindow:
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except Exception as e:
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self.update_status(f"Failed to initialize planning components: {e}")
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def plan_path(self):
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"""Plan path from A to B through hole using AI RRT*"""
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self.update_status("Starting AI RRT* path planning...")
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# 暂停仿真线程，避免规划期间并发 step 引入副作用
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def execute_three_stages(self):
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"""执行三阶段任务：当前位置→物体→A点→B点"""
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self.update_status("Starting three-stage execution...")
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# 暂停仿真以避免规划期间的副作用
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was_running = self.simulation_running
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if was_running:
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self.pause_simulation()
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try:
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# Get task points and object position
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# 获取配置中的任务点和物体位置
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task_points = self.config_loader.get_task_points()
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point_a = task_points['point_A']['position']
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point_b = task_points['point_B']['position']
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# Get transport object position from config
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transport_object_config = self.config_loader.get_full_config()['transport_object']
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object_position = transport_object_config['initial_position']
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# Get current joint configuration
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# 清除旧的可视化
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self._clear_visualizations()
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# ===================
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# 第一阶段：当前位置 → 物体
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# ===================
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self.update_status("Stage 1: Planning path from current position to object...")
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# 获取当前关节配置
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current_config = self.arm_controller.get_current_joint_positions()
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# Convert points to joint configurations using inverse kinematics
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self.update_status("Computing target configurations...")
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# Object position configuration
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# 计算物体位置的逆运动学
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config_object = self.arm_controller.inverse_kinematics(object_position, seed_angles=current_config)
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if config_object is None:
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raise RuntimeError("Cannot find joint configuration for object position")
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# A point configuration
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config_a = self.arm_controller.inverse_kinematics(point_a, seed_angles=config_object)
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if config_a is None:
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raise RuntimeError("Cannot find joint configuration for point A")
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# B point configuration
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config_b = self.arm_controller.inverse_kinematics(point_b, seed_angles=config_a)
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if config_b is None:
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raise RuntimeError("Cannot find joint configuration for point B")
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# Plan three path segments
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# Segment 1: Current position to object (ignore transport object collision)
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self.update_status("Planning path from current position to object...")
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# Temporarily ignore transport object for approaching it
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# 规划路径（忽略物体碰撞）
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self.collision_checker.ignore_transport_object = True
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try:
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path_to_object = self.path_planner.plan_auto(current_config, config_object)
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finally:
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# Restore collision checking for transport object
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self.collision_checker.ignore_transport_object = False
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# Segment 2: Object to A
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self.update_status("Planning path from object to A...")
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path_object_to_a = self.path_planner.plan_auto(config_object, config_a)
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# Segment 3: A to B (通用避障；若配置要求强制穿洞，内部会选择穿洞策略)
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self.update_status("Planning path from A to B...")
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path_a_to_b = self.path_planner.plan_auto(config_a, config_b)
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# Optimize paths separately to maintain segment information
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self.update_status("Optimizing path segments...")
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# Optimize path to object (ignore transport object collision)
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self.collision_checker.ignore_transport_object = True
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try:
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optimized_path_to_object = self.path_optimizer.optimize_path(path_to_object, self.collision_checker)
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finally:
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self.collision_checker.ignore_transport_object = False
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optimized_path_object_to_a = self.path_optimizer.optimize_path(path_object_to_a, self.collision_checker)
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optimized_path_a_to_b = self.path_optimizer.optimize_path(path_a_to_b, self.collision_checker)
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# Merge optimized paths (remove duplicate points)
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self.planned_path = (optimized_path_to_object[:-1] +
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optimized_path_object_to_a[:-1] +
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optimized_path_a_to_b)
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# Store segment boundaries
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self.object_index = len(optimized_path_to_object) - 1
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self.point_a_index = self.object_index + len(optimized_path_object_to_a) - 1
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path_length = len(self.planned_path)
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self.update_status(f"Path planning successful! Full path contains {path_length} waypoints")
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# Enable execute button
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self.execute_btn.config(state=tk.NORMAL)
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# Visualize path with segments
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self._visualize_path(self.planned_path)
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except Exception as e:
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import traceback
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self.update_status(f"Path planning failed: {str(e)}")
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print("Full traceback:")
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traceback.print_exc()
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self.planned_path = None
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self.execute_btn.config(state=tk.DISABLED)
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finally:
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# 规划完成后恢复仿真运行状态
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if was_running:
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self.start_simulation()
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def execute_path(self):
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"""Execute the planned path using pre-planned segments"""
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self.update_status("Starting three-stage execution using planned path...")
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# 可视化第一段路径（紫色）
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self._visualize_path_segment(optimized_path_to_object, [0.8, 0, 0.8], "To Object")
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try:
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# Check if planned path exists
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if self.planned_path is None:
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raise RuntimeError("No planned path available. Please run path planning first.")
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# Stage 1: Execute path to object using pre-planned segment
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# 执行第一段路径
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self.update_status("Stage 1: Moving to object...")
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path_to_object = self.planned_path[:self.object_index + 1]
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self.collision_checker.ignore_transport_object = True
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try:
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success = self.path_executor.execute_path(path_to_object, gripper_action=None)
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success = self.path_executor.execute_path(optimized_path_to_object, gripper_action=None)
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finally:
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self.collision_checker.ignore_transport_object = False
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if not success:
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raise RuntimeError("Stage 1 failed: Could not reach object")
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# Close gripper
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# 抓取物体
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self.update_status("Closing gripper at object...")
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if hasattr(self.arm_controller, 'close_gripper'):
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self.arm_controller.close_gripper()
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import time
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time.sleep(0.5)
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# After gripping, ignore transport object collision
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# 从现在开始忽略物体碰撞（因为已经抓取）
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self.collision_checker.ignore_transport_object = True
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# Stage 2: Execute path from object to A using pre-planned segment
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self.update_status("Stage 2: Moving to point A...")
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path_to_a = self.planned_path[self.object_index:self.point_a_index + 1]
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# ===================
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# 第二阶段：物体 → A点
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# ===================
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self.update_status("Stage 2: Planning path from object to point A...")
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success = self.path_executor.execute_path(path_to_a, gripper_action=None)
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# 计算A点的逆运动学
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config_a = self.arm_controller.inverse_kinematics(point_a, seed_angles=config_object)
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if config_a is None:
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raise RuntimeError("Cannot find joint configuration for point A")
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# 规划路径
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path_object_to_a = self.path_planner.plan_auto(config_object, config_a)
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optimized_path_object_to_a = self.path_optimizer.optimize_path(path_object_to_a, self.collision_checker)
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# 可视化第二段路径（绿色）
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self._visualize_path_segment(optimized_path_object_to_a, [0, 1, 0], "To A")
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# 执行第二段路径
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self.update_status("Stage 2: Moving to point A...")
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success = self.path_executor.execute_path(optimized_path_object_to_a, gripper_action=None)
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if not success:
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raise RuntimeError("Stage 2 failed: Could not reach point A")
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# Stage 3: Execute path from A to B using pre-planned segment
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self.update_status("Stage 3: Moving to point B...")
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path_to_b = self.planned_path[self.point_a_index:]
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# ===================
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# 第三阶段：A点 → B点
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# ===================
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self.update_status("Stage 3: Planning path from A to B...")
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success = self.path_executor.execute_path(path_to_b, gripper_action=None)
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# 计算B点的逆运动学
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config_b = self.arm_controller.inverse_kinematics(point_b, seed_angles=config_a)
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if config_b is None:
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raise RuntimeError("Cannot find joint configuration for point B")
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# 规划路径
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path_a_to_b = self.path_planner.plan_auto(config_a, config_b)
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optimized_path_a_to_b = self.path_optimizer.optimize_path(path_a_to_b, self.collision_checker)
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# 可视化第三段路径（蓝色）
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self._visualize_path_segment(optimized_path_a_to_b, [0, 0, 1], "To B")
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# 执行第三段路径
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self.update_status("Stage 3: Moving to point B...")
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success = self.path_executor.execute_path(optimized_path_a_to_b, gripper_action=None)
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if not success:
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raise RuntimeError("Stage 3 failed: Could not reach point B")
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# Open gripper at B
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# 释放物体
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self.update_status("Opening gripper at point B...")
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if hasattr(self.arm_controller, 'open_gripper'):
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self.arm_controller.open_gripper()
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time.sleep(0.5)
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# 添加任务点标记
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self._add_point_markers(object_position, point_a, point_b)
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self.update_status("All three stages completed successfully!")
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except Exception as e:
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import traceback
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self.update_status(f"Path execution error: {str(e)}")
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self.update_status(f"Execution error: {str(e)}")
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print("Full traceback:")
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traceback.print_exc()
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finally:
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# Restore collision checking
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# 恢复碰撞检测
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self.collision_checker.ignore_transport_object = False
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def _visualize_path(self, path):
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"""Visualize the planned path in PyBullet"""
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try:
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# Remove old visualization if exists
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if hasattr(self, 'path_visualization'):
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for line_id in self.path_visualization:
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p.removeUserDebugItem(line_id)
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# Remove old markers if exists
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if hasattr(self, 'point_markers'):
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for marker_id in self.point_markers:
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p.removeBody(marker_id)
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# 恢复仿真运行状态
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if was_running:
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self.start_simulation()
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def _visualize_path_segment(self, path, color, label):
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"""可视化单个路径段 - 显示实际执行轨迹"""
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if not hasattr(self, 'path_visualization'):
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self.path_visualization = []
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self.point_markers = []
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# Get task points and object position for markers
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task_points = self.config_loader.get_task_points()
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point_a_pos = task_points['point_A']['position']
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point_b_pos = task_points['point_B']['position']
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object_pos = self.config_loader.get_full_config()['transport_object']['initial_position']
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# Draw path as lines between waypoints（仅用 KDL FK 计算，不改仿真状态）
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for i in range(len(path) - 1):
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start_pos, _ = self.arm_controller.forward_kinematics(path[i])
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end_pos, _ = self.arm_controller.forward_kinematics(path[i + 1])
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# Choose color based on segment
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if hasattr(self, 'object_index') and i < self.object_index:
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# Path from initial to object - Purple
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color = [0.8, 0, 0.8]
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elif hasattr(self, 'point_a_index') and i < self.point_a_index:
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# Path from object to A - Green
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color = [0, 1, 0]
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else:
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# Path from A to B - Blue
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color = [0, 0, 1]
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# Draw line
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line_id = p.addUserDebugLine(
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start_pos, end_pos,
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lineColorRGB=color,
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lineWidth=2,
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physicsClientId=self.physics_client
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# 导入numpy用于插值计算
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import numpy as np
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# 对每两个waypoint之间进行插值，显示实际轨迹
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for i in range(len(path) - 1):
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current_config = path[i]
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target_config = path[i + 1]
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# 计算插值步数（与path_executor相同的逻辑）
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distance = np.linalg.norm(np.array(target_config) - np.array(current_config))
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if distance < 0.001: # 跳过太近的点
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continue
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# 使用与path_executor相同的参数
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velocity_scaling = self.config_loader.get_full_config()['path_planning']['execution']['velocity_scaling']
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timestep = self.config_loader.get_full_config()['simulation']['timestep']
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move_time = distance / velocity_scaling
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num_steps = max(5, int(move_time / timestep)) # 至少5步以保证平滑
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# 插值并绘制
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prev_pos = None
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for step in range(num_steps + 1):
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ratio = step / num_steps
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interpolated = (
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np.array(current_config) * (1 - ratio) +
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np.array(target_config) * ratio
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)
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self.path_visualization.append(line_id)
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# Add markers for object, A and B points
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# Marker for object - Orange sphere
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sphere_obj = p.createVisualShape(
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p.GEOM_SPHERE,
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radius=0.05,
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rgbaColor=[1, 0.5, 0, 0.8], # Orange
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physicsClientId=self.physics_client
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)
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marker_obj = p.createMultiBody(
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baseVisualShapeIndex=sphere_obj,
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basePosition=object_pos,
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physicsClientId=self.physics_client
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)
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self.point_markers.append(marker_obj)
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# Marker for point A - Yellow sphere
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sphere_a = p.createVisualShape(
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p.GEOM_SPHERE,
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radius=0.05,
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rgbaColor=[1, 1, 0, 0.8], # Yellow
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physicsClientId=self.physics_client
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)
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marker_a = p.createMultiBody(
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baseVisualShapeIndex=sphere_a,
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basePosition=point_a_pos,
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physicsClientId=self.physics_client
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)
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self.point_markers.append(marker_a)
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# Marker for point B - Red sphere
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sphere_b = p.createVisualShape(
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p.GEOM_SPHERE,
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radius=0.05,
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rgbaColor=[1, 0, 0, 0.8], # Red
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physicsClientId=self.physics_client
|
||||
)
|
||||
marker_b = p.createMultiBody(
|
||||
baseVisualShapeIndex=sphere_b,
|
||||
basePosition=point_b_pos,
|
||||
physicsClientId=self.physics_client
|
||||
)
|
||||
self.point_markers.append(marker_b)
|
||||
|
||||
# Add text labels
|
||||
p.addUserDebugText(
|
||||
"OBJ", object_pos,
|
||||
textColorRGB=[1, 0.5, 0],
|
||||
textSize=1.5,
|
||||
physicsClientId=self.physics_client
|
||||
)
|
||||
p.addUserDebugText(
|
||||
"A", point_a_pos,
|
||||
textColorRGB=[1, 1, 0],
|
||||
textSize=1.5,
|
||||
physicsClientId=self.physics_client
|
||||
)
|
||||
p.addUserDebugText(
|
||||
"B", point_b_pos,
|
||||
textColorRGB=[1, 0, 0],
|
||||
textSize=1.5,
|
||||
physicsClientId=self.physics_client
|
||||
)
|
||||
|
||||
# 可选：不恢复任何机器人状态（可视化不改状态）
|
||||
|
||||
except Exception as e:
|
||||
self.update_status(f"Path visualization failed: {e}")
|
||||
|
||||
# 计算插值点的末端位置
|
||||
pos, _ = self.arm_controller.forward_kinematics(interpolated.tolist())
|
||||
|
||||
if prev_pos is not None:
|
||||
# 画线段
|
||||
line_id = p.addUserDebugLine(
|
||||
prev_pos, pos,
|
||||
lineColorRGB=color,
|
||||
lineWidth=2,
|
||||
physicsClientId=self.physics_client
|
||||
)
|
||||
self.path_visualization.append(line_id)
|
||||
|
||||
prev_pos = pos
|
||||
|
||||
self.update_status(f"Visualized {label} path: {len(path)} waypoints with interpolation")
|
||||
|
||||
def _clear_visualizations(self):
|
||||
"""清除所有可视化元素"""
|
||||
# 清除路径线条
|
||||
if hasattr(self, 'path_visualization'):
|
||||
for line_id in self.path_visualization:
|
||||
p.removeUserDebugItem(line_id)
|
||||
self.path_visualization = []
|
||||
|
||||
# 清除点标记
|
||||
if hasattr(self, 'point_markers'):
|
||||
for marker_id in self.point_markers:
|
||||
p.removeBody(marker_id)
|
||||
self.point_markers = []
|
||||
|
||||
def _add_point_markers(self, object_pos, point_a_pos, point_b_pos):
|
||||
"""添加任务点标记"""
|
||||
if not hasattr(self, 'point_markers'):
|
||||
self.point_markers = []
|
||||
|
||||
# 物体标记 - 橙色
|
||||
sphere_obj = p.createVisualShape(
|
||||
p.GEOM_SPHERE,
|
||||
radius=0.05,
|
||||
rgbaColor=[1, 0.5, 0, 0.8],
|
||||
physicsClientId=self.physics_client
|
||||
)
|
||||
marker_obj = p.createMultiBody(
|
||||
baseVisualShapeIndex=sphere_obj,
|
||||
basePosition=object_pos,
|
||||
physicsClientId=self.physics_client
|
||||
)
|
||||
self.point_markers.append(marker_obj)
|
||||
|
||||
# A点标记 - 黄色
|
||||
sphere_a = p.createVisualShape(
|
||||
p.GEOM_SPHERE,
|
||||
radius=0.05,
|
||||
rgbaColor=[1, 1, 0, 0.8],
|
||||
physicsClientId=self.physics_client
|
||||
)
|
||||
marker_a = p.createMultiBody(
|
||||
baseVisualShapeIndex=sphere_a,
|
||||
basePosition=point_a_pos,
|
||||
physicsClientId=self.physics_client
|
||||
)
|
||||
self.point_markers.append(marker_a)
|
||||
|
||||
# B点标记 - 红色
|
||||
sphere_b = p.createVisualShape(
|
||||
p.GEOM_SPHERE,
|
||||
radius=0.05,
|
||||
rgbaColor=[1, 0, 0, 0.8],
|
||||
physicsClientId=self.physics_client
|
||||
)
|
||||
marker_b = p.createMultiBody(
|
||||
baseVisualShapeIndex=sphere_b,
|
||||
basePosition=point_b_pos,
|
||||
physicsClientId=self.physics_client
|
||||
)
|
||||
self.point_markers.append(marker_b)
|
||||
|
||||
# 添加文本标签
|
||||
p.addUserDebugText("OBJ", object_pos, textColorRGB=[1, 0.5, 0], textSize=1.5, physicsClientId=self.physics_client)
|
||||
p.addUserDebugText("A", point_a_pos, textColorRGB=[1, 1, 0], textSize=1.5, physicsClientId=self.physics_client)
|
||||
p.addUserDebugText("B", point_b_pos, textColorRGB=[1, 0, 0], textSize=1.5, physicsClientId=self.physics_client)
|
||||
|
||||
def _reset_camera_view(self):
|
||||
"""Reset camera to default view"""
|
||||
|
||||
@ -206,10 +206,14 @@ class AIRRTStarPlanner:
|
||||
if np.linalg.norm(new_config - np.array(goal_config)) < GOAL_TOLERANCE:
|
||||
# 找到路径，提取并返回
|
||||
path = self._extract_path(new_node)
|
||||
|
||||
|
||||
# 确保路径以精确的目标配置结束
|
||||
if not np.allclose(path[-1], goal_config, atol=1e-6):
|
||||
path.append(goal_config.tolist() if isinstance(goal_config, np.ndarray) else goal_config)
|
||||
|
||||
# 缓存成功配置
|
||||
self._cache_success_configs(path)
|
||||
|
||||
|
||||
return path
|
||||
else:
|
||||
self.params.update(success=False)
|
||||
|
||||
@ -70,19 +70,15 @@ class PathExecutor:
|
||||
return True
|
||||
|
||||
def _move_to_configuration(self, target_config: List[float]) -> bool:
|
||||
|
||||
|
||||
current_config = self.arm_controller.get_current_joint_positions()
|
||||
|
||||
|
||||
|
||||
|
||||
distance = np.linalg.norm(
|
||||
np.array(target_config) - np.array(current_config)
|
||||
)
|
||||
|
||||
|
||||
if distance < self.position_tolerance:
|
||||
return True
|
||||
|
||||
|
||||
|
||||
|
||||
move_time = distance / self.velocity_scaling
|
||||
num_steps = int(move_time / self.timestep) + 1
|
||||
|
||||
|
||||
Loading…
Reference in New Issue
Block a user