Spatial Iterative Learning Control for Robots in Contact with Unknown Environments

Yuting Guo, Guangzhu Peng, Dengxiu Yu, Chenguang Yang

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

Abstract

A spatial iterative control method is developed for robots to interact with an unknown environment at a desired level. Motivated by the human adaptive behaviour, the developed robot controller can adapt its reference trajectory to maintain a desired interaction force by designing a learning law. Considering the uncertain dynamics of the robot, an adaptive control algorithm integrating neural networks is employed to enable the robot to track the reference trajectory, so that the interaction performance is achieved. Through Lyapunov theory, signals of the closed-loop system are analyzed and proven to be convergent. Simulation results exhibit that the learning controller for the robot has adaptive properties in contacting tasks.

Original languageEnglish
Title of host publicationICIT 2024 - 2024 25th International Conference on Industrial Technology
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350340266
DOIs
StatePublished - 2024
Event25th IEEE International Conference on Industrial Technology, ICIT 2024 - Bristol, United Kingdom
Duration: 25 Mar 202427 Mar 2024

Publication series

NameProceedings of the IEEE International Conference on Industrial Technology
ISSN (Print)2641-0184
ISSN (Electronic)2643-2978

Conference

Conference25th IEEE International Conference on Industrial Technology, ICIT 2024
Country/TerritoryUnited Kingdom
CityBristol
Period25/03/2427/03/24

Keywords

  • Adaptive control
  • contact tasks
  • motion adaptation
  • spatial iterative learning control

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