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对于移动操纵器的层次运动规划方法
Hanlin Chen1, Xizhe Zang1, Yubin Liu1
1State Key Laboratory of Robotics and Systems, Harbin Institute of Technology, Harbin 150001, China.
Sensors (Basel, Switzerland)
|August 12, 2023
概括
本研究介绍了一种用于移动操纵器的新型层次运动计划器. 该计划器有效地处理3D障碍物和实时操纵器重新配置,在速度和成功率方面表现优于传统方法.
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
- 运动规划 运动规划
背景情况:
- 移动操纵器需要复杂的运动规划,无论是基础还是手臂运动.
- 实时适应动态环境和操纵器配置至关重要.
- 现有的方法经常遇到3D障碍,或者需要大量的计算资源.
研究的目的:
- 为移动操纵器开发一个分层的运动计划器,能够进行自主,实时的配置更改.
- 为应对动作规划中3D障碍和计算效率所带来的挑战.
- 与现有算法相比,提高成功率并减少计算时间.
主要方法:
- 一个两层次的层次规划器:移动基地的全球2D路径规划和基地和操纵器的本地3D规划.
- 用一个优化的A*算法来生成全局路径.
- 采用基于启发式采样的算法,以实时有效,无碰撞的操纵器配置搜索.
主要成果:
- 基于启发式采样的算法在计算时间,成功率和配置质量方面表现优于随机采样.
- 提出的方法有效地处理3D障碍.
- 这种方法避免了大量的内存需求,并减少了全球计划生成时间.
结论:
- 开发的层次运动计划器为复杂的3D环境中的移动操纵器导航提供了高效和有效的解决方案.
- 启发式采样方法显著提高了实时避免碰撞和配置规划.
- 这种方法是传统运动规划技术的可行替代方案,提供了更好的性能和资源效率.
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