摘要
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.
| 源语言 | 英语 |
|---|---|
| 页(从-至) | 2113-2118 |
| 页数 | 6 |
| 期刊 | IFAC-PapersOnLine |
| 卷 | 59 |
| 期 | 20 |
| DOI | |
| 出版状态 | 已出版 - 1 8月 2025 |
| 活动 | 23th IFAC Symposium on Automatic Control in Aerospace, ACA 2025 - Harbin, 中国 期限: 2 8月 2025 → 6 8月 2025 |
指纹
探究 'MARL Control of On-Orbit Peg-in-Hole Assembly in Macro-Micro Robots' 的科研主题。它们共同构成独一无二的指纹。引用此
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