解决手识别偏移的问题，增加手跟踪(未完成)

src/openarm_camera/openarm_camera/camera_pub.py

@@ -8,8 +8,8 @@ import numpy as np
 from camera_info_manager import CameraInfoManager
 from sensor_msgs.msg import CameraInfo
 
-CAMERA_WIDTH = int(1280) 
+CAMERA_WIDTH = 1280
-CAMERA_HEIGHT = int(480)
+CAMERA_HEIGHT = 480
 
 FRAME_WIDTH = int(CAMERA_WIDTH / 2)
 FRAME_HEIGHT = int(CAMERA_HEIGHT / 2)

src/openarm_camera/openarm_camera/hand_to_moveit_planning.py

@@ -0,0 +1,156 @@
+import rclpy
+from rclpy.node import Node
+from rclpy.action import ActionClient
+import numpy as np
+import time
+
+from moveit_msgs.action import MoveGroup
+from moveit_msgs.msg import Constraints, PositionConstraint
+from geometry_msgs.msg import PointStamped, PoseStamped
+from shape_msgs.msg import SolidPrimitive
+
+import tf2_ros
+import tf2_geometry_msgs
+
+
+
+class HandFollowMoveIt(Node):
+    def __init__(self):
+        super().__init__('hand_follow_moveit')
+
+        self.client = ActionClient(self, MoveGroup, '/move_action')
+
+        self.last_sent = time.time()
+        self.send_period = 0.3   # 约 3 Hz
+
+        self.p_prev = None
+
+        self.plan_period = 1.0       # 秒（规划频率）
+        self.min_delta = 0.05        # m，手移动超过才重新规划
+        self.z_min = 0.15            # 防止撞桌
+        self.z_max = 0.60
+        self.latest_hand = None
+        self.last_target = None
+
+        self.base_frame = 'openarm_body_link0'
+
+        # ====== TF ======
+        self.tf_buffer = tf2_ros.Buffer()
+        self.tf_listener = tf2_ros.TransformListener(self.tf_buffer, self)
+
+        # ====== 订阅 ======
+        self.sub = self.create_subscription(
+            PointStamped,
+            '/hand_3d',
+            self.hand_cb,
+            10
+        )
+        self.timer = self.create_timer(self.plan_period, self.plan_timer)
+
+        self.get_logger().info('Hand → MoveIt Planning node started')
+    # ---------- 回调 ----------
+    def hand_cb(self, msg):
+        try:
+            hand = self.tf_buffer.transform(
+                msg,
+                self.base_frame,
+                timeout=rclpy.duration.Duration(seconds=0.1)
+            )
+        except Exception:
+            return
+        print(f"手坐标（{self.base_frame}):{hand.point.x:.3f}, {hand.point.y:.3f}, {hand.point.z:.3f}")
+        self.latest_hand = np.array([
+            hand.point.x,
+            hand.point.y,
+            hand.point.z
+        ])
+
+    def update_hand(self, p):
+        """ p: np.array([x,y,z]) in base_link """
+
+        # 1️⃣ 限幅（按你机械臂改）
+        p[0] = np.clip(p[0], 0.25, 0.55)
+        p[1] = np.clip(p[1], -0.30, 0.30)
+        p[2] = np.clip(p[2], 0.25, 0.30)
+
+        # 2️⃣ 低通滤波
+        if self.p_prev is None:
+            self.p_prev = p
+            return
+
+        alpha = 0.2
+        p = alpha * p + (1 - alpha) * self.p_prev
+
+        # 3️⃣ 死区
+        if np.linalg.norm(p - self.p_prev) < 0.015:
+            return
+
+        # 4️⃣ 控制频率
+        if time.time() - self.last_sent < self.send_period:
+            return
+
+        self.send_goal(p)
+        self.p_prev = p
+        self.last_sent = time.time()
+
+    def send_goal(self, p):
+        pose = PoseStamped()
+        pose.header.frame_id = "openarm_body_link0"
+        pose.pose.position.x = float(p[0])
+        pose.pose.position.y = float(p[1])
+        pose.pose.position.z = float(p[2])
+        pose.pose.orientation.w = 1.0
+        # pose.pose.position.x = 0.0
+        # pose.pose.position.y = 0.153
+        # pose.pose.position.z = 0.262
+        goal = MoveGroup.Goal()
+        req = goal.request
+        req.group_name = "left_arm"
+        req.allowed_planning_time = 2.0
+        req.max_velocity_scaling_factor = 0.2
+
+        pc = PositionConstraint()
+        pc.header = pose.header
+        pc.link_name = "openarm_left_link7"
+
+        box = SolidPrimitive()
+        box.type = SolidPrimitive.BOX
+        box.dimensions = [0.02, 0.02, 0.02]
+        pc.constraint_region.primitives.append(box)
+        pc.constraint_region.primitive_poses.append(pose.pose)
+
+        constraints = Constraints()
+        constraints.position_constraints.append(pc)
+        req.goal_constraints.append(constraints)
+
+        self.client.wait_for_server()
+        self.client.send_goal_async(goal)
+            
+    def plan_timer(self):
+            if self.latest_hand is None:
+                return
+
+            # 限制 workspace
+            target = self.latest_hand.copy()
+            target[2] = np.clip(target[2], self.z_min, self.z_max)
+
+            # 判断是否值得重新规划
+            if self.last_target is not None:
+                if np.linalg.norm(target - self.last_target) < self.min_delta:
+                    return
+
+            self.last_target = target.copy()
+            self.send_goal(target)
+            print(f"发送新目标：{target[0]:.3f}, {target[1]:.3f}, {target[2]:.3f}")
+
+def main():
+    rclpy.init()
+    node = HandFollowMoveIt()
+    rclpy.spin(node)
+    rclpy.shutdown()
+    # while True:
+    #     p_hand_base = get_hand_3d()   # 你已有
+    #     node.update_hand(p_hand_base)
+
+if __name__ == "__main__":
+    main()

src/openarm_camera/openarm_camera/stereo_hand_depth_node.py

@@ -132,7 +132,7 @@ class StereoHandDepthNode(Node):
         if results.multi_hand_landmarks:
             wrist = results.multi_hand_landmarks[0].landmark[0]
 
-            u = int(wrist.x * w)
+            u = int(wrist.x * (w / 2))  # 注意这里是左图宽度
             v = int(wrist.y * h)
             p.header = msg.header
             p.point.x = float(u)
@@ -142,7 +142,7 @@ class StereoHandDepthNode(Node):
         # 转灰度
         left_gray = cv2.cvtColor(left_rect, cv2.COLOR_BGR2GRAY)
         right_gray = cv2.cvtColor(right_rect, cv2.COLOR_BGR2GRAY)
-        # cv2.imshow('left', left_gray)
+
 
         # 计算视差
         disparity = self.stereo.compute(left_gray, right_gray).astype(np.float32) / 16.0
@@ -150,11 +150,14 @@ class StereoHandDepthNode(Node):
         # ----------- 这里先用“假手点”（画面中心）-----------
         x = int(p.point.x)
         y = int(p.point.y)
-        print(f'Wrist pixel: ({x}, {y})')
+        cv2.circle(left_gray, (x, y), 5, (255, 0, 0), -1)
+        # print("left_gray.shape:", left_gray.shape)
+        # cv2.imshow('left', left_gray)
+        # print(f'Wrist pixel: ({x}, {y})')
         # ROI 取中值，稳很多
         roi = disparity[y-3:y+3, x-3:x+3]
         d = np.nanmedian(roi)
-        print(f'Disparity at wrist: {roi}')
+        # print(f'Disparity at wrist: {roi}')
 
         if d <= 0:
             return

src/openarm_camera/package.xml

@@ -6,6 +6,12 @@
   <description>TODO: Package description</description>
   <maintainer email="shen@todo.todo">shen</maintainer>
   <license>TODO: License declaration</license>
+  <exec_depend>rclpy</exec_depend>
+  <exec_depend>sensor_msgs</exec_depend>
+  <exec_depend>cv_bridge</exec_depend>
+  <exec_depend>usb_cam</exec_depend>
+  <exec_depend>stereo_image_proc</exec_depend>
+
 
   <test_depend>ament_copyright</test_depend>
   <test_depend>ament_flake8</test_depend>

src/openarm_camera/setup.py

@@ -32,6 +32,7 @@ setup(
             'camera_node = openarm_camera.camera:main',
             'camera_pub_node = openarm_camera.camera_pub:main',
             'stereo_hand_depth_node = openarm_camera.stereo_hand_depth_node:main',
+            'hand_to_moveit_planning = openarm_camera.hand_to_moveit_planning:main',
         ],
     },
 )