新型针阵列夹爪可自适应抓握并识别凹凸地形形状
A Pin-Array Structure for Gripping and Shape Recognition of Convex and Concave Terrain Profiles
- 采用针阵列结构实现对凸凹地形的自适应抓握
- 可同步测量地形表面形状，支持3D地形建图
- 适合极端环境下移动机器人的稳定攀爬与环境感知
本文提出一种可抓握并识别地形形状的夹爪，适用于极端环境中的移动机器人。多肢攀爬机器人在悬崖、洞壁等粗糙地形上表现良好，但在未知自然环境中可能因误抓或抓点丢失而失稳或卡住。为解决此问题，需具备自适应抓握不规则地形能力的夹爪，不仅用于抓握，还需精确测量地形表面形状。本文设计的夹爪通过引入针阵列结构，能够同时抓握凸形和凹形地形，并实时测量地形轮廓。通过原型验证了夹爪的抓握与地形识别性能，结果表明该设计在3D地形建图和不规则地形自适应抓握方面均具有良好效果。
原文摘要 · Abstract (English)
This paper presents a gripper capable of grasping and recognizing terrain shapes for mobile robots in extreme environments. Multi-limbed climbing robots with grippers are effective on rough terrains, such as cliffs and cave walls. However, such robots may fall over by misgrasping the surface or getting stuck owing to the loss of graspable points in unknown natural environments. To overcome these issues, we need a gripper capable of adaptive grasping to irregular terrains, not only for grasping but also for measuring the shape of the terrain surface accurately. We developed a gripper that can grasp both convex and concave terrains and simultaneously measure the terrain shape by introducing a pin-array structure. We demonstrated the mechanism of the gripper and evaluated its grasping and terrain recognition performance using a prototype. Moreover, the proposed pin-array design works well for 3D terrain mapping as well as adaptive grasping for irregular terrains.
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