Trajectory Tracking Control of a Tracked Mobile Robot with a Passive Bio-Inspired Suspension∗

Zhengchao Li, Xingjian Jing, Jinyong Yu

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

4 Citations (Scopus)

Abstract

A tracked mobile robot with a novel passive suspension system has been developed. The novel passive suspension system is constructed by using a bio-inspired animal-limb-like structure. A double layer nonlinear model predictive control (NMPC) architecture is adopted for the optimization of trajectory tracking. The upper layer NMPC is performed at a low frequency to optimize the global trajectory tracking performance, and the lower layer NMPC is performed at a high frequency to capture the local dynamics, like slippage and obstacle negotiation. An indoor environment experiment demonstrates that the novel passive suspension can efficiently absorb the strong shock induced by the process of obstacle crossing and hence guarantee the smooth motion and the double layer NMPC can effectively improve the trajectory tracking accuracy.

Original languageEnglish
Title of host publicationProceedings - 2019 IEEE International Conference on Mechatronics, ICM 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages114-119
Number of pages6
ISBN (Electronic)9781538669594
DOIs
Publication statusPublished - 24 May 2019
Event2019 IEEE International Conference on Mechatronics, ICM 2019 - Ilmenau, Germany
Duration: 18 Mar 201920 Mar 2019

Publication series

NameProceedings - 2019 IEEE International Conference on Mechatronics, ICM 2019

Conference

Conference2019 IEEE International Conference on Mechatronics, ICM 2019
Country/TerritoryGermany
CityIlmenau
Period18/03/1920/03/19

Keywords

  • passive bio-inspired suspension system
  • tracked mobile robot
  • trajectory tracking control

ASJC Scopus subject areas

  • Artificial Intelligence
  • Human-Computer Interaction
  • Automotive Engineering
  • Mechanical Engineering
  • Control and Optimization
  • Industrial and Manufacturing Engineering

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