使用改进的A*算法为一台轮腿机器人设计跨越障碍物路径的规划
Jinliang Lu1, Ming Pi1, Guoxin Zeng1
1School of Information and Control Engineering, Southwest University of Science and Technology, Mianyang 621010, China.
Sensors (Basel, Switzerland)
|September 27, 2025
概括
这项研究增强了轮腿机器人的A*路径规划,改善了复杂环境中的障碍回避. 新的算法大大减少了路径节点和计划时间,以实现高效的自主导航.
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
- 路径规划算法 路径规划算法
背景情况:
- 带轮腿的机器人在复杂的静态环境中面临着避免障碍物和地形谈判的挑战.
- 有效的路线规划对于自主导航和运营效率至关重要.
研究的目的:
- 为轮腿机器人引入增强的A*路径规划算法.
- 提高障碍物穿越效率和复杂环境中的运动稳定性.
主要方法:
- 集成的跳转点搜索,动态加权启发式,和连续跳转约束进入A*算法.
- 扩展了8个社区规则,以支持对角跳跃.
- 实现了冗余点去除和贝齐尔曲线平滑,以优化路径.
主要成果:
- 与标准A*相比,搜索节点 (从542到78) 减少了85%.
- 将计划时间缩短到0.0032秒.
- 在穿越复杂结构和改善运动稳定性方面表现出增强的性能.
结论:
- 增强的A*算法显著提高了复杂静态环境中的轮腿机器人的路径规划效率.
- 该算法增强了自主导航能力和运动稳定性.
- 这项研究有助于机器人系统更有效的实时路径规划.
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