为提高多智能体任务完成效率以及降低成本,基于阿克曼无人车模型设计了滑模控制器, 实现了跟随车对于期望轨迹跟踪。采用双曲正切函数代替指数趋近律中的符号函数, 保证切换函数具有连续性。证明了新构造趋近律作用下系统的收敛性。基于树莓派4B和ROS搭建了低成本无人车实验平台, 完成了ROS软件功能设计, 包括无人车平台的导航、建图、TF变换等功能。针对多无人车系统完成了组网操作, 使得无人车能够进行传感器数据共享并通过TF变换关系求得相对位置信息。最后基于所设计的滑模控制器在实机平台完成实验, 得到编队控制性能曲线图并进行了定性定量分析。

In order to improve task execution efficiency of muti-agent system and reduce costs, the sliding mode controller is designed based on dynamical model of Akerman unmanned vehicle, which realizes the tracking of the expected trajectory by the follower vehicle.The hyperbolic tangent function is adopted to replace the symbolic function in exponential reaching law for ensuring the continuity of the switch function.The convergence of the system is proved based on the new reaching law.A low-cost unmanned vehicle experiment platform is built based on ROS and Raspberry Pi 4B.ROS software is designed, including navigation, mapping, TF transformation and other functions of unmanned vehicle platform.The networking operation is completed for multi-unmanned vehicle system, so that the sensor data of unmanned vehicles can be shared and the relative position information between unmanned vehicles can be obtained through TF transformation.Finally, an experiment is performed on the unmanned vehicle experiment platform according to the sliding mode controller.The formation control performance curve is obtained and analyzed quantitatively and qualitatively.