Haptic identification of objects using a modular soft robotic gripper
Bianca S. Homberg, Robert K. Katzschmann, Mehmet R. Dogar, Daniela Rus
Abstract
This work presents a soft hand capable of robustly grasping and identifying objects based on internal state measurements. A highly compliant hand allows for intrinsic robustness to grasping uncertainty, but the specific configuration of the hand and object is not known, leaving undetermined if a grasp was successful in picking up the right object. A soft finger was adapted and combined to form a three finger gripper that can easily be attached to existing robots, for example, to the wrist of the Baxter robot. Resistive bend sensors were added within each finger to provide a configuration estimate sufficient for distinguishing between a set of objects. With one data point from each finger, the object grasped by the gripper can be identified. A clustering algorithm to find the correspondence for each grasped object is presented for both enveloping grasps and pinch grasps. This hand is a first step towards robust proprioceptive soft grasping.
BibTeX
@inproceedings{iros2015_hapticidentifica,
title = {Haptic identification of objects using a modular soft robotic gripper},
author = {Bianca S. Homberg and Robert K. Katzschmann and Mehmet R. Dogar and Daniela Rus},
booktitle = {IROS 2015},
year = {2015}
}