基于RRT*Smart-AD算法的双操纵器臂的合作动态运动规划
Houyun Long1, Guang Li1, Fenglin Zhou1
1School of Mechanical Engineering, Hunan University of Technology, Zhuzhou 412001, China.
Sensors (Basel, Switzerland)
|September 28, 2023
概括
一个新的RRT*Smart-AD运动计划器在动态环境中增强了双臂机器人的合作. 它确保了智能制造应用程序的避开障碍物和光滑,无碰撞的轨迹.
科学领域:
- 机器人和智能系统 机器人和智能系统
- 人工智能的人工智能
- 制造业 工程 制造工程
背景情况:
- 双臂合作操作对于智能制造至关重要,需要先进的运动规划.
- 像RRT和RRT*Smart这样的现有算法在处理动态环境和双重操纵者的合作任务方面存在局限性.
- 需要改进运动规划,以解决双臂系统的采样,优化和动态适应性.
研究的目的:
- 为在动态环境中运行的双臂机器人提出一种新的运动规划器,RRT*Smart-AD.
- 通过解决采样方法,路径优化和动态适应性来增强合作运动规划.
- 确保生成的轨迹满足避障,差异和物理碰撞的限制.
主要方法:
- 引入了动态A*成本函数采样方法与智能信标采样相结合.
- 实施了改善计算效率的路径修剪策略.
- 制定了动态区域路径修复和再生的战略,以提高适应能力.
- 利用粒子集群优化 (PSO) 来优化五进制的非统一的理性B-splines (NURBS) 轨迹,考虑速度和加速等约束因素.
主要成果:
- 与偏向的RRT*和RRT*Smart.相比,RRT*Smart-AD算法在双机器人臂的合作动态路径规划中表现出卓越的性能.
- 在动态场景中,生成了符合差异和物理碰撞约束的平滑运动轨迹.
- 成功解决了双臂机器人的避障能力和动态特性.
结论:
- RRT*Smart-AD提供了一个强大的解决方案,用于智能工厂中双臂机器人的合作运动规划.
- 拟议的方法为避免障碍物和动态路径规划提供了重要的实际工程价值.
- 这项研究为在复杂环境中运行的其他机器人系统的路径规划提供了理论参考.
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