【摘要】 为了使双机械臂能够在复杂的环境中完成协同运动任务，提出了一种基于机器人操作系统(robot operating system, ROS)的改进路径规划算法。首先，根据双机械臂的坐标系，推导出相关的约束关系，为减小轨迹误差设计一种双机械臂标定方法，准确计算出双机械臂基座标齐次变换关系；其次，为了优化机械臂的运动规划算法，对传统的快速随机搜索树(rapidly-exploring random tree, RRT)算法进行偏置采样，融合(probabilistic road map, PRM)算法对路径进行二次优化，使其获得最短路径；最后，通过五次多项式对获得的路径进行轨迹优化。整个方案通过ROS控制实际机器人进行算法验证，实际结果证明，所提方案规划效率更高。更多还原

【Abstract】 In order to enable the dual robotic arms to accomplish cooperative motion tasks in complex environments, an improved path planning algorithm based on robot operating system(ROS) is proposed in this paper.First, based on the coordinate system of the dual robotic arms, we derive the relevant constraints, design a dual robotic arm calibration method to reduce the trajectory error, and accurately calculate the base scale flush transformation relationship of the dual robotic arms; second, in order to optimize the motion planning algorithm of the robotic arms, the traditional rapidly-exploring random tree(RRT) algorithm is Secondly, to optimize the motion planning algorithm of the robot arm, the traditional rapidly-exploring random tree(RRT) algorithm is biased and sampled, and the path is optimized twice by incorporating the probabilistic road map(PRM) algorithm to obtain the shortest path; finally, the obtained path is optimized by using a quintuple polynomial.The whole scheme is verified by ROS control of the actual robot, and the actual results prove that the proposed scheme is more efficient in planning.更多还原