基于虚拟仿真预测的服务机器人路径规划研究

Trajectory Planning of Service Robot Based on Virtual Simulation Prediction

针对遥操作服务机器人受网络时延影响造成控制信号传输中断的问题,提出了一种虚拟仿真预测平台对遥操作系统中主从两端机器人进行运动预判,提高遥操作服务机器人的控制准确度。对服务机器人建立孪生模型,实现了虚实机器人的深度融合,能够有效反映真实机器人的多维信息。为服务机器人系统建立了人机交互界面,实现了对机器人的实时控制与状态显示。利用机器人的正逆运动学模型,实现了虚实机器人同步控制和轨迹实时映射。采用快速扩展随机树算法(Rapidly Exploring Random Tree,RRT)实现了复杂约束下的无碰撞路径规划。通过实验验证了设计的人机交互界面能够准确控制机器人的运动,RRT算法能够规划出使机器人避开障碍物并到达目标点的路径,真实机器人能跟随孪生模型的运行轨迹实现避障。

Aiming at the problem that the teleoperation service robot is affected by the network delay and the control signal transmission is interrupted,a virtual simulation prediction platform is proposed to predict the motion of the real robot and improve the control accuracy of the teleoperation service robot.The twin model of service robot is established to realize the deep fusion of virtual and real robot,which can effectively reflect the multi-dimensional information of real robot.A human-machine interaction interface is established for the service robot system,achieving real-time control and status display of the robot.By utilizing the forward and inverse kinematic models of the robot,synchronous control and real-time trajectory mapping of virtual and real robots are achieved.Rapidly exploring random tree(RRT)algorithm is used to realize collision-free path planning under complex constraints.Experiments show that the RRT algorithm can plan the path for the robot to avoid obstacles and reach the target point,and the real robot can follow the trajectory of the digital model to avoid obstacles.