Journal of Bionic Engineering ›› 2024, Vol. 21 ›› Issue (2): 852-865.doi: 10.1007/s42235-023-00449-4

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Brain Cognition Mechanism‑Inspired Hierarchical Navigation Method for Mobile Robots

Qiang Zou1; Chengdong Wu1; Ming Cong2; Dong Liu2   

  1. 1 Faculty of Robot Science and Engineering, Northeastern University, Shenyang 110819, China  2 School of Mechanical Engineering, Dalian University of Technology, Dalian 116024, China
  • 出版日期:2024-01-30 发布日期:2024-04-08
  • 通讯作者: Qiang Zou E-mail:zouq@mail.neu.edu.cn
  • 作者简介:Qiang Zou1; Chengdong Wu1; Ming Cong2; Dong Liu2

Brain Cognition Mechanism‑Inspired Hierarchical Navigation Method for Mobile Robots

Qiang Zou1; Chengdong Wu1; Ming Cong2; Dong Liu2   

  1. 1 Faculty of Robot Science and Engineering, Northeastern University, Shenyang 110819, China  2 School of Mechanical Engineering, Dalian University of Technology, Dalian 116024, China
  • Online:2024-01-30 Published:2024-04-08
  • Contact: Qiang Zou E-mail:zouq@mail.neu.edu.cn
  • About author:Qiang Zou1; Chengdong Wu1; Ming Cong2; Dong Liu2

摘要: Autonomous navigation is a fundamental problem in robotics. Traditional methods generally build point cloud map or dense feature map in perceptual space; due to lack of cognition and memory formation mechanism, traditional methods exist poor robustness and low cognitive ability. As a new navigation technology that draws inspiration from mammal’s navigation, bionic navigation method can map perceptual information into cognitive space, and have strong autonomy and environment adaptability. To improve the robot’s autonomous navigation ability, this paper proposes a cognitive map-based hierarchical navigation method. First, the mammals’ navigation-related grid cells and head direction cells are modeled to provide the robots with location cognition. And then a global path planning strategy based on cognitive map is proposed, which can anticipate one preferred global path to the target with high efciency and short distance. Moreover, a hierarchical motion controlling method is proposed, with which the target navigation can be divided into several sub-target navigation, and the mobile robot can reach to these sub-targets with high confdence level. Finally, some experiments are implemented, the results show that the proposed path planning method can avoid passing through obstacles and obtain one preferred global path to the target with high efciency, and the time cost does not increase extremely with the increase of experience nodes number. The motion controlling results show that the mobile robot can arrive at the target successfully only depending on its self-motion information, which is an efective attempt and refects strong bionic properties.

关键词: Bionic navigation , · Spatial localization cells , · Global path planning , · Hierarchical motion controlling

Abstract: Autonomous navigation is a fundamental problem in robotics. Traditional methods generally build point cloud map or dense feature map in perceptual space; due to lack of cognition and memory formation mechanism, traditional methods exist poor robustness and low cognitive ability. As a new navigation technology that draws inspiration from mammal’s navigation, bionic navigation method can map perceptual information into cognitive space, and have strong autonomy and environment adaptability. To improve the robot’s autonomous navigation ability, this paper proposes a cognitive map-based hierarchical navigation method. First, the mammals’ navigation-related grid cells and head direction cells are modeled to provide the robots with location cognition. And then a global path planning strategy based on cognitive map is proposed, which can anticipate one preferred global path to the target with high efciency and short distance. Moreover, a hierarchical motion controlling method is proposed, with which the target navigation can be divided into several sub-target navigation, and the mobile robot can reach to these sub-targets with high confdence level. Finally, some experiments are implemented, the results show that the proposed path planning method can avoid passing through obstacles and obtain one preferred global path to the target with high efciency, and the time cost does not increase extremely with the increase of experience nodes number. The motion controlling results show that the mobile robot can arrive at the target successfully only depending on its self-motion information, which is an efective attempt and refects strong bionic properties.

Key words: Bionic navigation , · Spatial localization cells , · Global path planning , · Hierarchical motion controlling