Real time contact surface prediction for grasping with complex geometries
Authors: Ander Etxezarreta Arruti
Date: 01.10.2022
Computers & Graphics
Abstract
The prediction of the contact areas for grasping different objects presents numerous problems with difficult and, most of the times, slow solutions. Common approaches simplify either the gripper or the shape of the object. This work integrates a fast collision detection system to the grasping process which approximates contact surfaces between arbitrarily complex grippers and grasped objects in realtime. Our collision detection method is based on the Voxelmap–Pointshell algorithm, which works with voxelized signed distance fields and point clouds of the scene. Concretely, the workspace of the gripper’s fingers is voxelized and a uniform surface point representation of the grasped object is generated. The intersection of both data structures during online grasping execution yields the approximate contact surfaces. In our setup, a 2-finger gripper with soft pads is used for grasping validation, performed through successful antipodal point detection under 1 ms. Simulated experimental results are provided for multiple shapes and resolutions.
BIB_text
author = {Ander Etxezarreta Arruti},
title = {Real time contact surface prediction for grasping with complex geometries},
journal = {Computers & Graphics},
pages = {66-72},
volume = {107},
keywds = {
Robotic grasping; Collision detection; Volumetric models
}
abstract = {
The prediction of the contact areas for grasping different objects presents numerous problems with difficult and, most of the times, slow solutions. Common approaches simplify either the gripper or the shape of the object. This work integrates a fast collision detection system to the grasping process which approximates contact surfaces between arbitrarily complex grippers and grasped objects in realtime. Our collision detection method is based on the Voxelmap–Pointshell algorithm, which works with voxelized signed distance fields and point clouds of the scene. Concretely, the workspace of the gripper’s fingers is voxelized and a uniform surface point representation of the grasped object is generated. The intersection of both data structures during online grasping execution yields the approximate contact surfaces. In our setup, a 2-finger gripper with soft pads is used for grasping validation, performed through successful antipodal point detection under 1 ms. Simulated experimental results are provided for multiple shapes and resolutions.
}
doi = {10.1016/j.cag.2022.07.007},
date = {2022-10-01},
}
