Custom soft robotic gripper sensor skins for haptic object visualization
Benjamin Shih, Dylan Drotman, Caleb Christianson, Zhaoyuan Huo, Ruffin White, Henrik I. Christensen, Michael T. Tolley
Abstract
Robots are becoming increasingly prevalent in our society in forms where they are assisting or interacting with humans in a variety of environments, and thus they must have the ability to sense and detect objects by touch. An ongoing challenge for soft robots has been incorporating flexible sensors that can recognize complex motions and close the loop for tactile sensing. We present sensor skins that enable haptic object visualization when integrated on a soft robotic gripper that can twist an object. First, we investigate how the design of the actuator modules impact bend angle and motion. Each soft finger is molded using a silicone elastomer, and consists of three pneumatic chambers which can be inflated independently to achieve a range of complex motions. Three fingers are combined to form a soft robotic gripper. Then, we manufacture and attach modular, flexible sensory skins on each finger to measure deformation and contact. These sensor measurements are used in conjunction with an analytical model to construct 2D and 3D tactile object models. Our results are a step towards soft robot grippers capable of a complex range of motions and proprioception, which will help future robots better understand the environments with which they interact, and has the potential to increase physical safety in human-robot interaction. Please see the accompanying video for additional details.
BibTeX
@inproceedings{iros2017_customsoftroboti,
title = {Custom soft robotic gripper sensor skins for haptic object visualization},
author = {Benjamin Shih and Dylan Drotman and Caleb Christianson and Zhaoyuan Huo and Ruffin White and Henrik I. Christensen and Michael T. Tolley},
booktitle = {IROS 2017},
year = {2017}
}