基于改进的RRT*算法,用于有限空间的挖掘机的避障轨迹规划方法
Shengjie Fu1,2, Chang Lin1,2, Zhaoyuan Yao3,4,5
1Fujian Key Laboratory of Green Intelligent Drive and Transmission for Mobile Machinery, Huaqiao University, Xiamen, 361021, China.
Scientific reports
|January 16, 2026
概括
本研究介绍了一种增强的RRT*算法,用于自动挖掘机轨迹规划,提高复杂环境中的效率和流性. 新方法确保无人驾驶操作的无碰撞,节能路径.
科学领域:
- 机器人和自动化 机器人和自动化
- 建筑工程工程 建筑工程
- 人工智能的人工智能
背景情况:
- 建筑机械正在向无人自主操作过渡.
- 挖掘机需要复杂的轨迹规划,以适应复杂和狭窄的环境.
- 现有的算法可能缺乏自主任务的效率和流性.
研究的目的:
- 为自动挖掘机提出一个避障轨迹规划方案.
- 在限制条件下提高路径搜索效率和轨迹质量.
- 为了实现操作持续时间和运动流的多目标优化.
主要方法:
- 开发了一个模拟模型用于挖掘机机制和环境.
- 增强了基于环境参数的启发式搜索和基于目标的自适应策略的RRT*算法.
- 利用五进制非统一的理性B-Spline (NURBS) 曲线来优化桶尖轨迹.
主要成果:
- 路径长度减少了3.65%,代数减少了64.15%,计算时间减少了67.9%.
- 改善了33.4%的轨道平滑性.
- 生成无碰撞,平滑和节能的轨迹.
结论:
- 改进的RRT*算法显著提高了自动挖掘机的性能.
- 这种方法确保了无人操作的高效率和机械可靠性.
- 这种方法在具有挑战性的环境中有效用于自主挖掘机导航.
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