Vision-based foothold contact reasoning using curved surface patches

D. Kanoulas, Chengxu Zhou, Anh Nguyen, Georgios Kanoulas, D. Caldwell, N. Tsagarakis
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引用次数: 20

Abstract

Reasoning about contacts between a legged robot's foot and the ground is a critical aspect of locomotion in natural terrains. This interaction becomes even more critical when the robot must move on rough surfaces. This paper presents a new visual contact analysis, based on curved patches that model local contact surfaces both on the sole of the robot's foot and in the terrain. The focus is on rigid, flat feet that represent the majority of the designs for current humanoids, but we also show how the introduced framework could be extended to other foot profiles, such as spherical feet. The footholds are localized visually in the environment's point cloud through a fast patch fitting process and a contact analysis between patches on the sole of the foot and in the surrounding environment. These patches aim to compose a spatial patch map for contact reasoning. We experimentally validate the introduced visionbased framework, using range data for rough terrain stepping demonstrations on the COMAN and WALK-MAN humanoids.
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基于视觉的曲面块触点推理
推理有腿机器人的脚与地面之间的接触是在自然地形中运动的一个关键方面。当机器人必须在粗糙的表面上移动时,这种相互作用变得更加重要。本文提出了一种新的视觉接触分析方法,该方法基于曲面块来模拟机器人脚底和地形上的局部接触面。重点是刚性,平脚,代表了大多数的设计为目前的类人,但我们也展示了如何引入的框架可以扩展到其他足廓,如球形脚。通过快速贴片拟合过程以及脚底贴片与周围环境之间的接触分析,可以在环境的点云中直观地定位立足点。这些斑块旨在组成一个空间斑块图用于接触推理。我们通过实验验证了引入的基于视觉的框架,使用距离数据在COMAN和WALK-MAN类人机器人上进行了崎岖地形的步进演示。
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