引用本文:欧林林,陈浩,肖云涛,程诚,俞立.满足复杂要求的机器人最优巡回控制系统设计与实现[J].控制理论与应用,2016,33(2):172~180.[点击复制]
OU Lin-lin,CHEN Hao,XIAO Yun-tao,CHENG Cheng,YU Li.Design and implement of optimal patrolling control system to satisfy the complex requirements[J].Control Theory and Technology,2016,33(2):172~180.[点击复制]
满足复杂要求的机器人最优巡回控制系统设计与实现
Design and implement of optimal patrolling control system to satisfy the complex requirements
摘要点击 3232  全文点击 2016  投稿时间：2014-12-02  修订日期：2015-08-06
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DOI编号  10.7641/CTA.2016.41119
  2016,33(2):172-180
中文关键词  路径规划  巡回控制  线性时序逻辑  模糊逻辑
英文关键词  motion planning  patrolling control  linear temporal logic  fuzzy logic
基金项目  国家自然科学基金项目(61273116), 浙江省自然科学基金项目(LY15F030015), 国家高新技术研究发展计划项目(2014AA041601–05), 机器人技术 与系统国家重点实验室开放基金项目(SKLRS–2013–MS–06)资助.
作者单位E-mail
欧林林* 浙江工业大学 linlinou@zjut.edu.cn 
陈浩 浙江工业大学  
肖云涛 浙江工业大学  
程诚 浙江工业大学  
俞立 浙江工业大学  
中文摘要
      本文结合线性时序逻辑理论与模糊控制方法, 设计并实现了一种满足复杂任务需求的移动机器人巡回控 制系统, 它既能够针对复杂时序任务进行路径规划, 又能够对机器人进行模糊控制实现路径跟踪. 首先, 基于线性 时序逻辑理论, 确定能够满足复杂巡回任务需求的全局最优路径. 接着, 根据所获得的最优路径, 采用模糊控制方 法设计轨迹跟踪控制器, 使其通过实时位姿反馈对机器人进行路径跟踪控制. 仿真结果验证了移动机器人巡回控制 系统的有效性. 最后, 基于E-Puck移动机器人构建了能够满足复杂任务需求的移动机器人巡回控制实验系统. 基于 所提出的最优巡回路径规划算法和模糊控制器设计方法, 通过图像处理、数据通信、算法加载等软件模块的实现完 成了满足复杂任务需求的移动机器人巡回控制.
英文摘要
      By combining the linear temporal logic theory and the fuzzy control method, a patrolling control system is presented in this paper, which enables the robot to perform complex temporal tasks. It can not only search the optimal path for complex sequential tasks, but also can realize the path tracking by using the fuzzy control method. Firstly, based on the theory of linear temporal logic (LTL), the global optimal path satisfying the demand of complex task is determined. Then, the fuzzy logic controller is designed for the trajectory tracking. It can actualize the optimal path tracking according to the feedback of the real-time position and orientation of the robot. Additionally, the simulation results show the effectiveness of the proposed patrolling control system. Finally, a patrolling control system satisfying the demand of complex task is established on the basis of the E-Puck robot, which includes image processing, data communications, algorithm loading and other software modules. The experiment shows that the complex patrolling control task is accomplished by using the proposed optimal patrolling path planning algorithm and the fuzzy control method.