| 基于内发动机机制的移动机器人自主路径规划方法 |
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| 引用本文： | 张晓平,阮晓钢,肖尧,谢瓦达哈,柴洁.基于内发动机机制的移动机器人自主路径规划方法[J].控制与决策,2018,33(9):1605-1611. |
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| 作者姓名： | 张晓平 阮晓钢 肖尧 谢瓦达哈 柴洁 |
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| 作者单位： | 1. 北京工业大学信息学部，北京100124,1. 北京工业大学信息学部，北京100124,1. 北京工业大学信息学部，北京100124,1. 北京工业大学信息学部，北京100124,1. 北京工业大学信息学部，北京100124 |
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| 基金项目： | 国家自然科学基金项目(61375086)；北京市自然科学基金项目(4174083)；北京市自然科学基金项目/北京市教育委员会科技计划重点项目(KZ201610005010). |
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| 摘 要： | 基于内发动机机制,为移动机器人建立一种新的路径规划方法.将已有内发动机机制中基于状态的好奇心函数扩展为基于动作的好奇心函数,并建立相应的动作选择机制,更符合生物可解释性.设计障碍物分布环境下的移动机器人状态能量函数,用于决定学习的方向.实验结果表明,所建立的方法能够有效地帮助机器人学习环境知识,实现不同初始状态下的避障导航任务.同时,能量函数的设计不依赖于具体环境,即使目标点发生改变,机器人也能通过重新学习到达目标,体现出方法的高度自主性和非任务性.
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| 关 键 词： | 内发动机 路径规划 移动机器人 操作条件反射 |
Mobile robot autonomous path planning method based on intrinsic motivation mechanism |
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| ZHANG Xiao-ping,RUAN Xiao-gang,XIAO Yao,SIE Quattara and CHAI Jie.Mobile robot autonomous path planning method based on intrinsic motivation mechanism[J].Control and Decision,2018,33(9):1605-1611. |
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| Authors: | ZHANG Xiao-ping RUAN Xiao-gang XIAO Yao SIE Quattara and CHAI Jie |
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| Affiliation: | 1. Faculty of Information Technology,Beijing University of Technology,Beijing100124,China;2. Beijing Key Laboratory of Computational Intelligence and Intelligent System,Beijing University of Technology,Beijing100124,China,1. Faculty of Information Technology,Beijing University of Technology,Beijing100124,China;2. Beijing Key Laboratory of Computational Intelligence and Intelligent System,Beijing University of Technology,Beijing100124,China,1. Faculty of Information Technology,Beijing University of Technology,Beijing100124,China;2. Beijing Key Laboratory of Computational Intelligence and Intelligent System,Beijing University of Technology,Beijing100124,China,1. Faculty of Information Technology,Beijing University of Technology,Beijing100124,China;2. Beijing Key Laboratory of Computational Intelligence and Intelligent System,Beijing University of Technology,Beijing100124,China and 1. Faculty of Information Technology,Beijing University of Technology,Beijing100124,China;2. Beijing Key Laboratory of Computational Intelligence and Intelligent System,Beijing University of Technology,Beijing100124,China |
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| Abstract: | Based on the intrinsic motivation mechanism, this paper builds up a new kind of path planning method. The curiosity function existing in such a mechanism is extended from state-based to motion-based, and the corresponding motion choosing mechanism is designed, which is more biologically explicable. The energy function of the mobile robot under the environment with obstacles is designed, which is used to decide the learning direction. Simulation results show that the proposed path planning method can help the robot learn its environment, and achieve obstacle-free navigation from any start position. What is more, the energy function is environment independent, and even though the target position changes, the robot can still complete the tasks through relearning, which proves that the proposed method is with high autonomy and not task specific. |
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