基于ARM-Linux的爬壁机器人控制器研究

针对人工船舶除锈的效率低、危险性高、成本高等问题,研制出爬壁机器人进行船舶除锈。采用了上、下位机的分布式控制方案,对基于ARM-Linux的爬壁机器人控制器进行研究,包括遥感器、比较器及其组成电路。通过引用强化学习算法Q-Leaning算法,实现了爬壁机器人的强化学习循迹,改进了传统PID等算法无法针对环境进行最优化动作策略选择的缺点,提高爬壁机器人在不同环境下循迹的准确性。实验结果表明,基于ARM-Linux的爬壁机器人控制系统性能较好,可以满足控制器要求。

Research on controller of wall climbing robot based on ARM Linux

Aiming at the low efficiency , high risk and high cost in manual ship descaling , the wall-climbing robot is developed .This paper adopts the distributed control scheme of host and slave machine to research the controller of the wall -climbing robot based on ARM-Linux, including the sensor, the comparator, and the composition of the circuit.By using the reinforcement learning algorithm Q-Leaning algorithm , the reinforcement learning tracking of wall-climbing robot is realized .The weakness that traditional PID and other algorithms that can 't optimize the action strategy for environment are improved and the wall-climbing robot in different environments tracking accuracy is raised .The experiment results show that the control system of the wall-climbing robot based on ARM-Linux can perform better and meet the requirements of the controller .