用球体近似机器人模型，提升碰撞检测效率。
Foam: A Tool for Spherical Approximation of Robot Geometry
- 从URDF文件自动生成球体组合的简化几何模型。
- 碰撞检测速度提升显著，精度损失微小。
- 适合需要快速距离查询的机器人仿真与规划场景。
机器人应用中常需使用球体等基本几何形状，尤其在需要高效距离查询时。手动构建球体模型耗时且易出错。本文提出Foam工具，可从输入的通用机器人描述格式（URDF）文件生成机器人几何的球体近似模型。Foam提供鲁棒的预处理流程以修复网格缺陷，并支持多种配置参数控制球化程度与近似精度，输出仅由球体构成碰撞几何的URDF文件。我们在多个标准机器人模型上验证了Foam在常见任务中的表现，结果显示碰撞检查与距离查询性能显著提升，且与真实碰撞几何相比仅略有精度损失。我们已将该工具以开源Python库和容器化命令行应用形式发布，便于机器人领域广泛采用。
原文摘要 · Abstract (English)
Many applications in robotics require primitive spherical geometry, especially in cases where efficient distance queries are necessary. Manual creation of spherical models is time-consuming and prone to errors. This paper presents Foam, a tool to generate spherical approximations of robot geometry from an input Universal Robot Description Format (URDF) file. Foam provides a robust preprocessing pipeline to handle mesh defects and a number of configuration parameters to control the level and approximation of the spherization, and generates an output URDF with collision geometry specified only by spheres. We demonstrate Foam on a number of standard robot models on common tasks, and demonstrate improved collision checking and distance query performance with only a minor loss in fidelity compared to the true collision geometry. We release our tool as an open source Python library and containerized command-line application to facilitate adoption across the robotics community.
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