Compensating Pose Uncertainties Through Appropriate Gripper Finger Cutouts

Adam Wolniakowski, Andrej Gams, Lilita Kiforenko, Aljaz Kramberger, Dimitrios-Chrysostomos Chrysostomou, Ole Madsen, Konstantsin Miatliuk, Henrik Gordon Petersen, Frederik Hagelskjær, Anders Glent Buch, Aleš Ude, Norbert Krüger

Research output: Contribution to journalConference articleResearchpeer-review

48 Downloads (Pure)

Abstract

The gripper finger design is a recurring problem in many robotic grasping platforms used in industry. The task of switching the gripper configuration to accommodate for a new batch of objects typically requires engineering expertise, and is a lengthy and costly iterative trial-and-error process. One of the open challenges is the need for the gripper to compensate for uncertainties inherent to the workcell, e.g. due to errors in calibration, inaccurate pose estimation from the vision system, or object deformation. In this paper, we present an analysis of gripper uncertainty compensating capabilities in a sample industrial object grasping scenario for a finger that was designed using an automated simulation-based geometry optimization method [1, 2]. We test the developed gripper with a set of grasps subjected to structured perturbation in a simulation environment and in the real-world setting. We provide a comparison of the data obtained by using both of these approaches. We argue that the strong correspondence observed in results validates the use of dynamic simulation for the gripper finger design and optimization.
Original languageEnglish
JournalActa Mechanica et Automatica
Volume12
Issue number1
Pages (from-to)78-83
ISSN1898-4088
DOIs
Publication statusPublished - 2018
EventThe 12th International Conference Mechatronic Systems and Materials - Bialystok, Poland
Duration: 3. Jul 20168. Jul 2016
http://www.msm2016.pb.edu.pl/

Conference

ConferenceThe 12th International Conference Mechatronic Systems and Materials
CountryPoland
CityBialystok
Period03/07/201608/07/2016
Internet address

Fingerprint

Grippers
Uncertainty
Robotics
Calibration
Geometry
Computer simulation
Industry

Cite this

Wolniakowski, Adam ; Gams, Andrej ; Kiforenko, Lilita ; Kramberger, Aljaz ; Chrysostomou, Dimitrios-Chrysostomos ; Madsen, Ole ; Miatliuk, Konstantsin ; Petersen, Henrik Gordon ; Hagelskjær, Frederik ; Buch, Anders Glent ; Ude, Aleš ; Krüger, Norbert. / Compensating Pose Uncertainties Through Appropriate Gripper Finger Cutouts. In: Acta Mechanica et Automatica. 2018 ; Vol. 12, No. 1. pp. 78-83.
@inproceedings{ee8bbb1ef5c044e5aebc9a737c480225,
title = "Compensating Pose Uncertainties Through Appropriate Gripper Finger Cutouts",
abstract = "The gripper finger design is a recurring problem in many robotic grasping platforms used in industry. The task of switching the gripper configuration to accommodate for a new batch of objects typically requires engineering expertise, and is a lengthy and costly iterative trial-and-error process. One of the open challenges is the need for the gripper to compensate for uncertainties inherent to the workcell, e.g. due to errors in calibration, inaccurate pose estimation from the vision system, or object deformation. In this paper, we present an analysis of gripper uncertainty compensating capabilities in a sample industrial object grasping scenario for a finger that was designed using an automated simulation-based geometry optimization method [1, 2]. We test the developed gripper with a set of grasps subjected to structured perturbation in a simulation environment and in the real-world setting. We provide a comparison of the data obtained by using both of these approaches. We argue that the strong correspondence observed in results validates the use of dynamic simulation for the gripper finger design and optimization.",
author = "Adam Wolniakowski and Andrej Gams and Lilita Kiforenko and Aljaz Kramberger and Dimitrios-Chrysostomos Chrysostomou and Ole Madsen and Konstantsin Miatliuk and Petersen, {Henrik Gordon} and Frederik Hagelskj{\ae}r and Buch, {Anders Glent} and Aleš Ude and Norbert Kr{\"u}ger",
year = "2018",
doi = "10.2478/ama-2018-0013",
language = "English",
volume = "12",
pages = "78--83",
journal = "Acta Mechanica et Automatica",
issn = "1898-4088",
publisher = "Bialystok University of Technology",
number = "1",

}

Compensating Pose Uncertainties Through Appropriate Gripper Finger Cutouts. / Wolniakowski, Adam; Gams, Andrej ; Kiforenko, Lilita; Kramberger, Aljaz; Chrysostomou, Dimitrios-Chrysostomos; Madsen, Ole; Miatliuk, Konstantsin; Petersen, Henrik Gordon; Hagelskjær, Frederik; Buch, Anders Glent; Ude, Aleš; Krüger, Norbert.

In: Acta Mechanica et Automatica, Vol. 12, No. 1, 2018, p. 78-83.

Research output: Contribution to journalConference articleResearchpeer-review

TY - GEN

T1 - Compensating Pose Uncertainties Through Appropriate Gripper Finger Cutouts

AU - Wolniakowski, Adam

AU - Gams, Andrej

AU - Kiforenko, Lilita

AU - Kramberger, Aljaz

AU - Chrysostomou, Dimitrios-Chrysostomos

AU - Madsen, Ole

AU - Miatliuk, Konstantsin

AU - Petersen, Henrik Gordon

AU - Hagelskjær, Frederik

AU - Buch, Anders Glent

AU - Ude, Aleš

AU - Krüger, Norbert

PY - 2018

Y1 - 2018

N2 - The gripper finger design is a recurring problem in many robotic grasping platforms used in industry. The task of switching the gripper configuration to accommodate for a new batch of objects typically requires engineering expertise, and is a lengthy and costly iterative trial-and-error process. One of the open challenges is the need for the gripper to compensate for uncertainties inherent to the workcell, e.g. due to errors in calibration, inaccurate pose estimation from the vision system, or object deformation. In this paper, we present an analysis of gripper uncertainty compensating capabilities in a sample industrial object grasping scenario for a finger that was designed using an automated simulation-based geometry optimization method [1, 2]. We test the developed gripper with a set of grasps subjected to structured perturbation in a simulation environment and in the real-world setting. We provide a comparison of the data obtained by using both of these approaches. We argue that the strong correspondence observed in results validates the use of dynamic simulation for the gripper finger design and optimization.

AB - The gripper finger design is a recurring problem in many robotic grasping platforms used in industry. The task of switching the gripper configuration to accommodate for a new batch of objects typically requires engineering expertise, and is a lengthy and costly iterative trial-and-error process. One of the open challenges is the need for the gripper to compensate for uncertainties inherent to the workcell, e.g. due to errors in calibration, inaccurate pose estimation from the vision system, or object deformation. In this paper, we present an analysis of gripper uncertainty compensating capabilities in a sample industrial object grasping scenario for a finger that was designed using an automated simulation-based geometry optimization method [1, 2]. We test the developed gripper with a set of grasps subjected to structured perturbation in a simulation environment and in the real-world setting. We provide a comparison of the data obtained by using both of these approaches. We argue that the strong correspondence observed in results validates the use of dynamic simulation for the gripper finger design and optimization.

U2 - 10.2478/ama-2018-0013

DO - 10.2478/ama-2018-0013

M3 - Conference article

VL - 12

SP - 78

EP - 83

JO - Acta Mechanica et Automatica

JF - Acta Mechanica et Automatica

SN - 1898-4088

IS - 1

ER -