在线多触点运动重新规划人形机器人用语义3D Voxel 映射:ExOctomap
Masato Tsuru1,2, Adrien Escande3, Iori Kumagai2
1Graduate School of Engineering and Science, Osaka University, Toyonaka 560-8531, Japan.
Sensors (Basel, Switzerland)
|November 14, 2023
概括
本研究介绍了使用语义3D语音映射对人形机器人进行快速运动重新规划的方法. 扩展八角图允许在未知的环境中进行高效的导航和无碰撞的轨道规划.
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
- 计算机视觉 计算机视觉
背景情况:
- 人形机器人在未知的环境中导航需要高效的在线绘图和运动规划.
- 使用多边形网格或原始提取的传统方法在复杂,动态的环境中面临挑战.
研究的目的:
- 为人形机器人开发一种快速运动重新规划技术.
- 为了使在未知的领土上使用语义3D voxel 映射实现自主导航.
主要方法:
- 引入了一种创新的扩展八角图 (ExOctomap) 用于语义3D语音映射.
- 利用Octree结构来存储环境正常向量,Euclidean集群提取和主要组件分析.
- 实现了3D网格采样,用于高效的6D接触姿势搜索和无碰撞轨迹规划.
主要成果:
- 从位置查询中实现了语义可访问性的O ((log N) 效率.
- 在各种环境中证明了多接触运动的高效适应.
- 获得了接近实时的规划速度,每次接触13.8ms至115.7ms.
结论:
- 拟议的语义语音映射和运动重新规划框架显著增强了人形机器人的自主性.
- 扩展八角图为实时环境传感和导航提供了高效和可扩展的解决方案.
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