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Author:

Zhang, Jiahui (Zhang, Jiahui.) | Ruan, Xiaogang (Ruan, Xiaogang.) | Huang, Jing (Huang, Jing.) | Chai, Jie (Chai, Jie.) | Wu, Yue (Wu, Yue.)

Indexed by:

EI

Abstract:

Curiosity plays an important role in the development of biological cognition, which drives animals to explore unknown environments. Inspired by the research of psychology, this paper proposes a curiosity-based mobile robot path planning method with a mental energy function, which is suitable for robot state evaluation. In our proposed method, a novel mental energy function is designed to guide the learning direction of the robot in navigation task. The experimental results show that the novel method we proposed can effectively guide robot to learn environment information. By changing the simulation environment, robot can reach the end point through re-learning the environment, that reflects the autonomous learning ability and the environmental adaptability of robots. © 2019 IEEE.

Keyword:

Robot programming Mobile robots Motion planning

Author Community:

  • [ 1 ] [Zhang, Jiahui]Beijing University of Technology, Faculty of Information Technology, China
  • [ 2 ] [Zhang, Jiahui]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing, China
  • [ 3 ] [Ruan, Xiaogang]Beijing University of Technology, Faculty of Information Technology, China
  • [ 4 ] [Ruan, Xiaogang]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing, China
  • [ 5 ] [Huang, Jing]Beijing University of Technology, Faculty of Information Technology, China
  • [ 6 ] [Huang, Jing]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing, China
  • [ 7 ] [Chai, Jie]Beijing University of Technology, Faculty of Information Technology, China
  • [ 8 ] [Chai, Jie]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing, China
  • [ 9 ] [Wu, Yue]Beijing University of Technology, Faculty of Information Technology, China
  • [ 10 ] [Wu, Yue]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing, China

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Source :

Year: 2019

Page: 476-480

Language: English

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 2

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 6

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