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冗余操纵器的基于多任务的反碰撞轨迹规划
Suping Zhao1, Yushuang Du1, Chaobo Chen1
1College of Electronic Information Engineering, Xi'an Technological University, Xi'an 710021, China.
Biomimetics (Basel, Switzerland)
|November 26, 2024
概括
一个新的算法为执行多个任务的机器人手臂规划无碰撞路径. 这种特殊的编码遗传算法 (SEGA) 优化了任务顺序和关节运动,以有效地避免障碍.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 人工智能的人工智能
- 计算几何学的计算几何学
背景情况:
- 冗余操纵器在多任务执行中面临挑战,原因是障碍物.
- 任务顺序和联合轨迹受到环境约束的重大影响.
研究的目的:
- 开发一种有效的抗碰撞轨迹规划方法,用于执行多个任务的冗余操纵器.
- 优化任务区域和联合轨迹的顺序顺序,同时确保避免障碍.
主要方法:
- 一种特殊的编码遗传算法 (SEGA) 被提出用于基于多任务的反碰撞轨迹规划.
- 使用球形封闭盒和叠加理论建模空间占用和障碍物检测.
- 联合轨迹由六度多项式表示,并优化了六度系数.
主要成果:
- 这个问题通过优化任务区域序列,碰撞检测和联合轨迹来转化为参数优化问题.
- 在SEGA成本函数平衡端效应器路径长度和关节角度变化.
- 数字模拟验证了SEGA方法的有效性.
结论:
- 拟议的SEGA有效地解决了冗余操纵器的基于多任务的反碰撞轨迹规划.
- 该方法确保了顺的关节运动和在存在障碍物时的最佳路径规划.
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