MARL Control of On-Orbit Peg-in-Hole Assembly in Macro-Micro Robots

  • Hao Li*
  • , Xuchao Huang*
  • , Yibo Zhang
  • , Quan An*
  • , Yao Zhang*
  • *Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

Abstract

In recent years, on-orbit operations have become a research hotspot. Traditional on-orbit assembly using only robotic arms suffers from low precision. Therefore, this paper proposes a Macro-Micro Coordinated Robotic System (MMCRS) consisting of a robotic arm and a Stewart platform. The paper analyzes the kinematic characteristics of the MMCRS for the on-orbit peg-in-hole assembly problem and introduces a Multi-Agent Reinforcement Learning algorithm, Full-State MADDPG. A staged, variable-parameter reward function is designed, and the effectiveness of the algorithm is verified through simulations.

Original languageEnglish
Pages (from-to)2113-2118
Number of pages6
JournalIFAC-PapersOnLine
Volume59
Issue number20
DOIs
Publication statusPublished - 1 Aug 2025
Event23th IFAC Symposium on Automatic Control in Aerospace, ACA 2025 - Harbin, China
Duration: 2 Aug 20256 Aug 2025

Keywords

  • Dynamic Reward Function
  • Macro-Micro Coordinated Robots
  • MARL
  • On-Orbit Assembly
  • Peg-in-Hole

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