基于神经网络的全方位移动机器人运动稳定性研究

doi:10.13973/j.cnki.robot.180492

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叶长龙, 张思阳, 于苏洋, 姜春英. 基于神经网络的全方位移动机器人运动稳定性研究[J]. 机器人, 2019, 41(4): 443-451.DOI: 10.13973/j.cnki.robot.180492. YE Changlong, ZHANG Siyang, YU Suyang, JIANG Chunying. Research on Movement Stability of Omni-directional Mobile RobotBased on Neural Network. ROBOT, 2019, 41(4): 443-451. DOI: 10.13973/j.cnki.robot.180492.

摘要全方位移动机器人具有平面运动的3个自由度，运动灵活性高，被广泛应用到狭窄拥挤环境中．针对实验室开发的MY2轮在运动过程中的振动现象及轨迹误差问题，采用BP（反向传播）神经网络方法来解决．根据机器人的结构及运动特点，建立BP神经网络模型并分析及优化了BP神经网络参数．以BP神经网络模型为基础进行轨迹仿真实验，分析初值、不同速度及不同轨迹对模型的影响．结果表明基于合适的BP神经网络方法可以将轨迹误差控制在3 mm内，偏向转角误差小于3°，能够减缓机器人振动，提高轨迹精度．通过输入不同运动轨迹验证BP神经网络模型的普遍适用性，最后通过实验验证了仿真结果的正确性．

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	叶长龙
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关键词 ：全方位移动机器人, 运动稳定性, BP 神经网络, 轨迹精度

Abstract：The omnidirectional mobile robot with 3-degree-of-freedom in the plane has high flexibility and can be also applied in crowded and narrow environment. The BP (backpropagation) neural network method is used to solve the problems of the vibration phenomena and trajectory error of the MY2 wheel developed in the laboratory during movement. According to the structure and movement characteristics of the robot, the BP neural network model is established and the parameters of the BP neural network are optimized. Trajectory simulation experiments based on the BP neural network model are conducted. The impact of initial values, different speeds and different trajectories on model are analyzed. The consequence shows that the method based on the suitable BP neural network can keep the trajectory error within the range of 3 mm and the deflection angle error less than 3°, so the BP neural network can decrease the robot vibration and improve the trajectory accuracy. The universal applicability of the BP neural network model is verified by inputting different motion trajectories, and the correctness of simulation results are validated by experiments in the end.

Key words： omnidirectional mobile robot motion stability BP (backpropagation) neural network trajectory accuracy

收稿日期: 2018-08-03 录用日期: 2018-12-12

TP24

基金资助:辽宁省自然科学基金（20180520033）

通讯作者: 叶长龙,changlye@163.com E-mail: changlye@163.com

作者简介: 叶长龙(1974-),男,教授.研究领域:仿生机器人,机器人机构学.
张思阳(1992-),女,硕士生.研究领域:机器人机构设计与运动控制.

链接本文:

https://robot.sia.cn/CN/10.13973/j.cnki.robot.180492 或 https://robot.sia.cn/CN/Y2019/V41/I4/443

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