FHQ-RRT*:为移动机器人改进的路径规划算法,以更快地获得高质量的路径
Xingxiang Dong1, Yujun Wang1, Can Fang1
1College of Computer and Information Science, Southwest University, Chongqing 400715, China.
Sensors (Basel, Switzerland)
|April 12, 2025
概括
更快的高质量RRT* (FHQ-RRT*) 通过提高探索速度和路径质量来改善移动机器人路径规划. 与现有方法相比,这种新的算法实现了更低的路径成本和显著减少的规划时间.
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
- 计算机科学 计算机科学
背景情况:
- 快速探索随机树星 (RRT*) 算法是机器人路径规划的标准.
- 现有的RRT*方法经常遭受缓慢的融合和低于最佳的路径成本.
研究的目的:
- 引入更快,更高质量的RRT* (FHQ-RRT*),这是一个优化的算法,用于更快,更高质量的路径生成.
- 为了提高探索效率和移动机器人导航的路径质量.
主要方法:
- 实施了动态稀疏采样策略,以适应性调整树木生长.
- 介绍了一种新的节点创建方法,使用两截,三角不等式和KeyPoints.
- 制定了一个专注的重新布线策略,以优化在有价值地区的重新布线操作.
主要成果:
- 在四个不同的模拟地图中,FHQ-RRT*始终实现了最低的路径成本.
- 显著减少了规划时间:在圆形障碍地图中超过40%,在简单迷宫中77%,在复杂迷宫中56%,在狭窄环境中50%.
- 与其他路径规划算法相比,验证了优越的性能.
结论:
- FHQ-RRT*有效地比现有的算法更快地生成高质量的路径.
- 拟议的创新提高了移动机器人路径规划的速度和质量.
- 在复杂的环境中,FHQ-RRT*为高效的机器人导航提供了有希望的进步.
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