基于模糊神经网络的六足机器人自主导航闭环控制系统设计

doi:10.13973/j.cnki.robot.170252

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孔令文, 李鹏永, 杜巧玲. 基于模糊神经网络的六足机器人自主导航闭环控制系统设计[J]. 机器人, 2018, 40(1): 16-23.DOI: 10.13973/j.cnki.robot.170252. KONG Lingwen, LI Pengyong, DU Qiaoling. The Closed-Loop Control System Design of Hexapod Robot Autonomous Navigation Based on Fuzzy Neural Network. ROBOT, 2018, 40(1): 16-23. DOI: 10.13973/j.cnki.robot.170252.

摘要针对未知环境中六足机器人的自主导航问题，设计了一种基于模糊神经网络的自主导航闭环控制算法，并依据该算法设计了六足机器人的导航控制系统．算法融合了模糊控制的逻辑推理能力与神经网络的学习训练能力，并引入闭环控制方法对算法进行优化．所设计的控制系统由信息输入、模糊神经网络、指令执行以及信息反馈4个模块组成．环境及位置信息的感知由GPS（全球定位系统）传感器、电子罗盘传感器和超声波传感器共同完成．采用C语言重建模糊神经网络控制算法，并应用于该系统．通过仿真实验，从理论上论证了基于模糊神经网络的闭环控制算法性能优于开环控制算法，闭环控制算法能够减小六足机器人在遇到障碍物时所绕行的距离，行进速度提高了6.14%，行进时间缩短了8.74%．在此基础上，开展了实物试验．试验结果表明，该控制系统能够实现六足机器人自主导航避障控制功能，相对于开环控制系统，能有效地缩短行进路径，行进速度提高了5.66%，行进时间缩短了7.25%，验证了闭环控制系统的可行性和实用性．

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关键词 ：六足机器人, 自主导航, 模糊神经网络, 闭环控制, 环境感知

Abstract：For the autonomous navigation issue of hexapod robot in unknown environment, an autonomous navigation closed-loop control algorithm based on fuzzy neural network is proposed, and a navigation control system of hexapod robot is designed according to the algorithm. The algorithm combines the logical reasoning ability of fuzzy control with the learning and training ability of neural network, and introduces the closed-loop control method into optimization. The control system is composed of four modules:information input, fuzzy neural network, instruction execution and information feedback. The perception of environment and location information is completed by GPS (global positioning system) sensor, electronic compass sensor and ultrasonic sensor. The fuzzy neural network control algorithm is reconstructed by C language and is applied to the system. The simulation results show that the closed-loop control algorithm based on fuzzy neural network is better than the open-loop control algorithm theoretically. The closed-loop control algorithm can reduce the walking distance of the hexapod in the environment with obstacles, and the walking speed is increased by 6.14%, the walking time is shortened by 8.74%. On this basis, a physical test is carried out. The experimental results show that the control system can achieve the autonomous obstacle-avoidance control of the hexapod robot. Compared with the open-loop control system, the walking path can be shortened effectively, the walking speed is increased by 5.66% and the walking time is shortened by 7.25%, which verifies the feasibility and practicability of the closed-loop control system.

Key words： hexapod robot autonomous navigation fuzzy neural network closed-loop control environmental perception

收稿日期: 2017-04-12 录用日期: 2017-10-12

TP242

基金资助:吉林省教育厅“十三五”科学研究规划项目（JJKH20170800KJ）

通讯作者: 杜巧玲,duql@jlu.edu.cn E-mail: duql@jlu.edu.cn

作者简介: 孔令文(1992-),男,硕士生.研究领域:六足机器人控制与路径规划;
李鹏永(1992-),男,硕士生.研究领域:六足机器人控制与路径规划;
杜巧玲(1978-),女,博士,副教授.研究领域:无线传感器网络定位技术,机器人路径规划与导航,水质监测实时系统.

链接本文:

https://robot.sia.cn/CN/10.13973/j.cnki.robot.170252 或 https://robot.sia.cn/CN/Y2018/V40/I1/16

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