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基于多目标粒子群优化算法的机器人新型多目标轨迹规划方法
Jiahui Wang1, Yongbo Zhang1,2, Shihao Zhu1
1School of Aeronautic Science and Engineering, Beihang University, Beijing 100191, China.
本研究介绍了一种新的多目标轨迹规划方法,用于太空机器人,优化旅行时间,能量和流性. 该方法利用B-spline函数和改进的粒子群优化算法,以提高太空探索中的性能.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 太空探索 太空探索
- 计算优化计算优化
背景情况:
- 太空机器人的性能对于探索任务至关重要.
- 关键性能指标包括行程时间,能源消耗和轨道平滑度.
- 有效的轨迹规划对于最大限度地提高机器人功能至关重要.
研究的目的:
- 为太空机器人提出一个多目标轨迹规划方法.
- 为了优化关键的性能指数:旅行时间,能源消耗和流性.
- 确保轨迹符合太空任务的实际工程要求.
主要方法:
- 普马560机器人的动力学和动态分析.
- 使用第五阶B-spline函数构建联合空间轨迹.
- 通过改进的多目标粒子群优化 (MOPSO) 算法进行优化.
主要成果:
- 实现了机器人关节的连续位置,速度,加速度和冲动.
- 帕雷托阵线表现出良好的分布统一性,收性和多样性.
- 成功优化了多个目标,以满足工程需求.
结论:
- 提出的基于MOPSO的轨迹规划方法有效地平衡了多个绩效目标.
- 该方法提供了优化的轨迹,适用于现实世界的太空探索应用.
- 可视化证实了优化机器人运动的成功实施.
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