Emergency-response locomotion of hexapod robot with heuristic reinforcement learning using Q-learning

Ming Chieh Yang, Hooman Samani, Kening Zhu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

The locomotion of legged robot is often controlled by predefined gaits, and this approach works well when all joints and motors are operating normally. However, walking legged robots usually have high risk of being damaged during operation, causing the breakdown of the robotic joints. In this paper, we introduce a reinforcement learning based approach for the legged robot to generate real-time locomotion response to the emergence of locomotion breakdown. Our approach detects the functionality of the available joints, substitutes the pre-defined gaits with proper gait function accordingly, and upgrades the gait-generation function by Q-Learning for the proper locomotion.

Original languageEnglish
Title of host publicationInteractive Collaborative Robotics - 4th International Conference, ICR 2019, Proceedings
EditorsAndrey Ronzhin, Roman Meshcheryakov, Gerhard Rigoll
PublisherSpringer Nature
Pages320-329
Number of pages10
ISBN (Print)9783030261177
DOIs
Publication statusPublished - 2019
Event4th International Conference on Interactive Collaborative Robotics, ICR 2019 - Istanbul, Turkey
Duration: 20 Aug 201925 Aug 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11659 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference4th International Conference on Interactive Collaborative Robotics, ICR 2019
Country/TerritoryTurkey
CityIstanbul
Period20/08/1925/08/19

Keywords

  • Emergency response
  • Hexapod robot
  • Q-Learning
  • Reinforcement learning

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