Abstract
This paper presents a lobster-inspired design of a soft finger's contact surface for grasping with enhanced robustness. The lobsters, while living on the seabed with sediments of various sizes, sources, materials, and life forms, exhibit exceptional capabilities in object manipulation under-water using angled-claws with two fingers. By inspecting the geometric features of the lobster tooth, we proposed a series of finger surface designs molded with silicone. We tested the surface friction using traditional methods to shortlist our design pool, and further verified their performance using robotic arm grasping against a series of challenging objects from the EGAD, the Evolved Grasping Analysis Dataset. Results show that, in certain cases, the lobster-inspired finger surface design yields an enhanced grasping success rate by 56% at most than those without the surface. Furthermore, we propose a minimum setup for robotic grasping using NVidia Jetson Xavier, Intel RealSense D435, and the proposed soft gripper to be compatible with most robotic manipulators as a cost-effective configuration for shareable and reproducible research.
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@conference{Jiang2021LobsterInspired,
title = {Lobster-inspired Finger Surface Design for Grasping with Enhanced Robustness},
author = {Haiyang Jiang and Yonglin Jing and Ning Guo and Weijie Guo and Fang Wan and Chaoyang Song},
doi = {10.1109/RoboSoft51838.2021.9479215},
year = {2021},
date = {2021-04-12},
urldate = {2021-04-12},
booktitle = {IEEE International Conference on Soft Robotics (RoboSoft)},
address = {New Haven, CT, USA},
abstract = {This paper presents a lobster-inspired design of a soft finger's contact surface for grasping with enhanced robustness. The lobsters, while living on the seabed with sediments of various sizes, sources, materials, and life forms, exhibit exceptional capabilities in object manipulation under-water using angled-claws with two fingers. By inspecting the geometric features of the lobster tooth, we proposed a series of finger surface designs molded with silicone. We tested the surface friction using traditional methods to shortlist our design pool, and further verified their performance using robotic arm grasping against a series of challenging objects from the EGAD, the Evolved Grasping Analysis Dataset. Results show that, in certain cases, the lobster-inspired finger surface design yields an enhanced grasping success rate by 56% at most than those without the surface. Furthermore, we propose a minimum setup for robotic grasping using NVidia Jetson Xavier, Intel RealSense D435, and the proposed soft gripper to be compatible with most robotic manipulators as a cost-effective configuration for shareable and reproducible research.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}