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障碍回避轨迹规划研究 钻井和定材料 通过机械臂在煤矿上处理 钻井和定机器人
Siya Sun1,2, Sirui Mao3, Xusheng Xue1,2
1College of Mechanical Engineering, Xi'an University of Science and Technology, Xi'an 710054, China.
Sensors (Basel, Switzerland)
|November 9, 2024
概括
本研究介绍了一种改进的机器人臂轨迹规划算法,用于煤矿道挖掘,提高钻井效率并减少劳动力. 与传统方法相比,新方法显著加快了优化速度,并缩短了路径长度.
科学领域:
- 机器人和自动化 机器人和自动化
- 采矿工程 采矿工程 采矿工程
- 人工智能的人工智能
背景情况:
- 目前的煤矿道支持依赖于机械钻井和定,面临低效率和高劳动强度的挑战.
- 之前的研究开发了一个用于钻井机的机器人系统,需要对其机器人臂进行先进的轨迹规划.
研究的目的:
- 提高煤矿道运营的效率和生产率.
- 开发和验证一个改进的轨迹规划算法用于钻井和定任务中的机器人手臂.
主要方法:
- 使用改进的D-H参数方法建立了机器人手臂的动态模型.
- 用蒙特卡洛方法分析工作空间,结合反向动力学来定义可行的领域.
- 通过目标指导和双向树连接策略改进了Bi-RRT算法,并进一步增强了动态环境的人工潜力场.
主要成果:
- 改进的Bi-RRT算法显示,优化速度增加了69.8%.
- 与传统的RRT算法相比,轨迹长度减少了46.6%.
- 在ROS环境中的模拟证实了算法的有效性,提高了规划速度和效率.
结论:
- 提议改进的Bi-RRT轨迹规划算法有效地解决了当前煤矿道道支持系统的局限性.
- 该算法在优化速度和轨迹效率方面提供了显著的改进,为更高效和更安全的采矿操作铺平了道路.
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