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基于连续机器人改进的人工潜力场的预抓取运动规划方法.
Lihua Wang1,2, Zezhou Sun2, Yaobing Wang2
1School of Mechanical and Aerospace Engineering, Jilin University, Changchun 130025, China.
Sensors (Basel, Switzerland)
|November 25, 2023
概括
连续机器人现在可以使用改进的人工潜力场更好地捕获空间碎片. 这种方法增强了预抓动作计划,防止碎片逃逸,并实现了97.8%的成功率.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 航空航天工程 航空航天工程
- 太空碎片管理 太空碎片管理
背景情况:
- 保持太空环境的稳定性需要有效的积极碎片清除 (ADR).
- 连续机器人为ADR提供了独特的功能,因为它们具有超冗余的自由度和全臂抓取.
- 现有的方法可能会在预先抓住机动时与目标逃脱作斗争.
研究的目的:
- 为ADR任务中的连续机器人提出一种新的预抓动作计划方法.
- 通过防止目标逃逸,提高捕获空间碎片的可靠性.
- 提高ADR行动的成功率.
主要方法:
- 一种预抓动作计划策略,利用连续机器人的改进的人工潜力场 (APF).
- 在动作计划之前,对工作空间进行分析,以确保目标可访问性.
- 该APF包含空间旋转,吸引力 (位置和姿势) 和排斥力潜在场.
- 将连续机器人划分为交付和抓取部分,以优化运动.
主要成果:
- 拟议的APF方法有效地限制了抓住目标的运动,防止逃跑.
- 包括姿势潜力场在内显著改善了空间目标的预抓动作规划性能.
- 模拟证明了该方法的有效性,成功率高达97.8%.
结论:
- 改进的基于APF的运动规划方法对基于连续机器人的ADR有效.
- 姿势潜力场对于提高预先抓住空间目标的成功率至关重要.
- 这种方法有助于更安全,更可靠的空间碎片清除操作.
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