基于启发式动态规划的履带机器人路径跟随控制方法

针对移动机器人传统路径跟随控制方法需要人工调校参数、缺乏自主优化能力的问题,提出了一种基于启发式动态规划（Heuristic dynamic programming, HDP）的路径跟随控制方法。首先,设计履带式机器人路径跟随控制系统结构,建立了误差状态方程;其次,提出了一种基于HDP算法的路径跟随控制方法,综合误差性能指标和跟随稳定性指标设计了回报函数,采用多层前馈神经网络逼近评价器和执行器,并推导了网络参数的在线优化规则;最后,通过数值仿真和系统试验验证了HDP方法的路径跟随性能。试验结果证明,基于HDP算法的控制器跟随直线的平均误差绝对值为0.04m、均方根误差为0.06m;跟随钝角转向曲线的平均误差绝对值为0.01m、均方根误差为0.06m;跟随锐角转向曲线的平均误差绝对值为0.03m、均方根误差为0.09m。该方法不需要对控制参数进行反复调试就能够获得较好的控制效果,提高了移动机器人路径跟随控制方法的环境适应性和自主优化能力。

Path Following Control Method of Tracked Mobile Robot Based on Heuristic Dynamic Programming

Aiming at the problem that the traditional path following control method of mobile robot requires manual tuning parameters and lacks of self-optimization ability, a path following control method based on heuristic dynamic programming (HDP) was proposed. Firstly, the error state equation of the path following system was established based on the structure of tracked robot system. Secondly, a path following controller based on HDP algorithm was proposed. The return function was designed by synthesizing the error performance index and the following stability index. A multi-layer feedforward neural network was used to establish the actuator and evaluation modules, and the online optimization rules of network parameters were derived. Thirdly, the path following performance of HDP method was verified by numerical simulation and system test. The experimental results showed that the controller based on the HDP algorithm of the mean absolute error was 0.04m and the root mean square error was 0.06m when following a straight line, 0.01m and 0.06m when following a obtuse angle steering curve, and 0.03m and 0.09m when following an acute angle steering curve, and the method based on HDP can obtain high precision control effect without repeated debugging control parameters, and it improved the environmental adaptability and autonomous optimization ability of the path following control method for mobile robots.