A MPC-based Planner Applied on a Parallel Wheel-legged Robot for Obstacle Avoidance

  • Fei Guo*
  • , Huan Yu
  • , Wanhong Lin
  • , Shoukun Wang
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

A wheel-legged robot is equipped with Stewart parallel mechanism, constituting a reconfigurable robot which can change its wheelbase, robot body height, and achieve omnidirectional steering. The legged character effectively improves the terrain adaptability, which concerns our planning concentration. We introduced an optimization-based whole-body trajectory planning algorithm to navigate robot in rugged terrain. The planner combines terrain data and stability, allowing lower-level motion generator and controller to operate more efficiently. The Model Predictive Control(MPC)based method updates the footholds and CoG trajectories, which builds upon the support polygon constraints on optimization. The simulations of methodology working in several structure-obstacle scene demonstrated and compared the availability of approach.

Original languageEnglish
Title of host publicationProceedings of the 4th International Conference on Computer, Artificial Intelligence and Control Engineering, CAICE 2025
PublisherAssociation for Computing Machinery, Inc
Pages545-552
Number of pages8
ISBN (Electronic)9798400712647
DOIs
Publication statusPublished - 2 Jun 2025
Externally publishedYes
Event4th International Conference on Computer, Artificial Intelligence and Control Engineering, CAICE 2025 - Hefei, China
Duration: 10 Jan 202512 Jan 2025

Publication series

NameProceedings of the 4th International Conference on Computer, Artificial Intelligence and Control Engineering, CAICE 2025

Conference

Conference4th International Conference on Computer, Artificial Intelligence and Control Engineering, CAICE 2025
Country/TerritoryChina
CityHefei
Period10/01/2512/01/25

Keywords

  • Reconfigurable robot
  • Trajectory planning
  • Wheel-legged robot

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