在ROS Noetic版本的MoveIt中，使用IPTP算法对轨迹重规划的python函数

在ROS Noetic版本的MoveIt中，可以使用以下的Python函数来对轨迹进行重规划：

from moveit_msgs.msg import RobotTrajectory
from trajectory_msgs.msg import JointTrajectoryPoint
from moveit_msgs.msg import RobotState
from moveit_msgs.srv import GetPositionFKRequest, GetPositionFK

def interpolate_trajectory(traj, time_step):
    # Convert the input trajectory message to a RobotTrajectory object
    robot_traj = RobotTrajectory()
    robot_traj.deserialize(traj)
    
    # Get the number of points in the trajectory
    num_points = len(robot_traj.joint_trajectory.points)
    
    # Create a new trajectory message
    new_traj = RobotTrajectory()
    new_traj.joint_trajectory.joint_names = robot_traj.joint_trajectory.joint_names
    
    # Create a new robot state message
    robot_state = RobotState()
    robot_state.joint_state.name = robot_traj.joint_trajectory.joint_names
    
    # Create a service client to compute FK
    fk_client = rospy.ServiceProxy('/compute_fk', GetPositionFK)
    fk_request = GetPositionFKRequest()
    fk_request.header.frame_id = 'world'
    fk_request.fk_link_names = ['end_effector']
    
    # Iterate over the points in the trajectory and interpolate between them
    for i in range(num_points - 1):
        # Get the start and end points of the segment
        start_point = robot_traj.joint_trajectory.points[i]
        end_point = robot_traj.joint_trajectory.points[i+1]
        
        # Compute the time interval for the segment
        start_time = start_point.time_from_start.to_sec()
        end_time = end_point.time_from_start.to_sec()
        delta_time = end_time - start_time
        
        # Compute the number of intermediate points to add
        num_intermediate_points = int(delta_time / time_step)
        
        # Interpolate between the start and end points
        for j in range(num_intermediate_points):
            # Compute the time for the intermediate point
            t = start_time + (j+1) * time_step
            
            # Compute the joint values for the intermediate point
            joint_values = []
            for k in range(len(robot_traj.joint_trajectory.joint_names)):
                # Compute the start and end joint values for the segment
                start_joint_value = start_point.positions[k]
                end_joint_value = end_point.positions[k]
                
                # Interpolate between the start and end joint values
                joint_value = start_joint_value + (end_joint_value - start_joint_value) * (t - start_time) / delta_time
                
                # Add the joint value to the list
                joint_values.append(joint_value)
            
            # Set the joint values in the robot state message
            robot_state.joint_state.position = joint_values
            
            # Compute the FK for the end effector
            fk_request.robot_state = robot_state
            fk_response = fk_client(fk_request)
            
            # Create a new trajectory point with the interpolated joint values and FK solution
            new_point = JointTrajectoryPoint()
            new_point.positions = joint_values
            new_point.time_from_start = rospy.Duration.from_sec(t)
            new_point.velocities = [0.0] * len(robot_traj.joint_trajectory.joint_names)
            new_point.accelerations = [0.0] * len(robot_traj.joint_trajectory.joint_names)
            new_point.effort = [0.0] * len(robot_traj.joint_trajectory.joint_names)
            new_point.positions += fk_response.pose_stamped[0].pose.position
            new_point.velocities += [0.0] * 3
            new_point.accelerations += [0.0] * 3
            new_point.effort += [0.0] * 3
            
            # Add the new point to the new trajectory
            new_traj.joint_trajectory.points.append(new_point)
    
    # Return the new trajectory message
    return new_traj.serialize()

该函数的输入参数为一个轨迹消息（类型为`moveit_msgs/RobotTrajectory`）和一个时间步长（单位为秒），返回值为一个序列化的轨迹消息。该函数会对输入轨迹进行插值，以使得轨迹上的点之间的时间间隔均为给定的时间步长。插值的方式为线性插值，即对关节值进行插值，并利用插值后的关节值计算末端执行器的FK解。为了计算FK解，该函数使用了MoveIt中的`/compute_fk`服务。