Push Grasping with Humanoid Hands

Eadom Dessalene, C. Korpela, D. Lofaro
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Abstract

This paper contributes to the work of push-grasping by producing data-driven models on the effects of the chosen angle of approach for anthropomorphic hands. An overview of previous work on robotic grasping is first presented. Thousands of trials of push grasping experiments are then compared between rigid angled funnel configurations coupled with a Baxter Electric Gripper end effector and the anthropomorphic, 16 DOF Allegro Hand end effector, each at different approach angles of approach. Geometrical capture regions for each set of trials are gathered. Push grasping is then applied to the realm of ground vehicles by coupling a mobile manipulator robot with the Allegro Hand, gathering the capture region as the body of the mobile manipulator rotates in place.
用人形手推抓握
本文通过建立数据驱动的模型,对拟人化手选择的接近角度的影响做出了贡献。首先概述了机器人抓取的前期工作。成千上万次的推抓取实验比较了刚性角度漏斗配置与Baxter电动抓取端执行器和拟人化的16自由度Allegro手端执行器在不同进近角度下的推抓取实验。收集每组试验的几何捕获区域。通过将移动机械臂与Allegro Hand耦合,将推抓取应用于地面车辆领域,在移动机械臂本体原地旋转时采集抓取区域。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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