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Benchmarking Protocol for Grasp Planning Algorithms

Bekiroglu, Yasemin and Marturi, Naresh and Roa Garzon, Máximo Alejandro and Komlan, Maxime and Pardi, Tommaso and Grimm, Cindy and Balasubramanian, Ravi and Hang, Kaiyu and Stolkin, Rustam (2020) Benchmarking Protocol for Grasp Planning Algorithms. IEEE Robotics and Automation Letters, 5 (2), pp. 315-322. IEEE - Institute of Electrical and Electronics Engineers. doi: 10.1109/LRA.2019.2956411. ISSN 2377-3766.

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Official URL: https://ieeexplore.ieee.org/document/8917672

Abstract

Numerous grasp planning algorithms have been proposed since the 1980s. The grasping literature has expanded rapidly in recent years, building on greatly improved vision systems and computing power. Methods have been proposed to plan stable grasps on: known objects (exact 3D model is available), familiar objects (e.g. exploiting a-priori known grasps for different objects of the same category), or novel object shapes observed during task execution. Few of these methods have ever been compared in a systematic way, and objective performance evaluation of such complex systems remains problematic. Difficulties and confounding factors include: different assumptions and amounts of a-priori knowledge in different algorithms; different robots, hands, vision systems and setups in different labs; different choices or application needs for grasped objects. Also, grasp planning can use different grasp quality metrics (including empirical or theoretical stability measures), or other criteria, e.g. computational speed, or combination of grasps with reachability considerations. While acknowledging and discussing the outstanding difficulties surrounding this complex topic, we propose a methodology for reproducible experiments to compare the performance of a variety of grasp planning algorithms. Our protocol attempts to improve the objectivity with which different grasp planners are compared by minimising the influence of key components in the grasping pipeline, e.g. vision and pose estimation. The protocol is demonstrated by evaluating two different grasp planners: a state-of-the-art model-free planner, and a popular open-source model-based planner. We show results from real-robot experiments with a 7-DoF arm and 2-finger hand, and simulation-based evaluations.

Item URL in elib:https://elib.dlr.de/136150/
Document Type:Article
Title:Benchmarking Protocol for Grasp Planning Algorithms
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Bekiroglu, YaseminKTHUNSPECIFIED
Marturi, NareshUniversity of BirminghamUNSPECIFIED
Roa Garzon, Máximo AlejandroMaximo.Roa (at) dlr.dehttps://orcid.org/0000-0003-1708-4223
Komlan, MaximeUniversity of BirminghamUNSPECIFIED
Pardi, TommasoUNSPECIFIEDUNSPECIFIED
Grimm, CindyOregon State UniversityUNSPECIFIED
Balasubramanian, RaviOregon State UniversityUNSPECIFIED
Hang, KaiyuYale UniversityUNSPECIFIED
Stolkin, RustamUniversity of Birmingham, UKUNSPECIFIED
Date:April 2020
Journal or Publication Title:IEEE Robotics and Automation Letters
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:5
DOI :10.1109/LRA.2019.2956411
Page Range:pp. 315-322
Publisher:IEEE - Institute of Electrical and Electronics Engineers
ISSN:2377-3766
Status:Published
Keywords:benchmarking; grasping; grasp planning
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Space System Technology
DLR - Research area:Raumfahrt
DLR - Program:R SY - Space System Technology
DLR - Research theme (Project):R - On-Orbit Servicing [SY]
Location: Oberpfaffenhofen
Institutes and Institutions:Institute of Robotics and Mechatronics (since 2013) > Autonomy and Teleoperation
Deposited By: Roa Garzon, Dr. Máximo Alejandro
Deposited On:21 Sep 2020 11:27
Last Modified:21 Sep 2020 11:27

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