Collision Detection Accelerated: An Optimization Perspective
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21730%2F22%3A00362937" target="_blank" >RIV/68407700:21730/22:00362937 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.15607/RSS.2022.XVIII.039" target="_blank" >https://doi.org/10.15607/RSS.2022.XVIII.039</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.15607/RSS.2022.XVIII.039" target="_blank" >10.15607/RSS.2022.XVIII.039</a>
Alternative languages
Result language
angličtina
Original language name
Collision Detection Accelerated: An Optimization Perspective
Original language description
Collision detection between two convex shapes is an essential feature of any physics engine or robot motion planner. It has often been tackled as a computational geometry problem, with the Gilbert, Johnson and Keerthi (GJK) algorithm being the most common approach today. In this work we leverage the fact that collision detection is fundamentally a convex optimization problem. In particular, we establish that the GJK algorithm is a specific sub-case of the well-established Frank-Wolfe (FW) algorithm in convex optimization. We introduce a new collision detection algorithm by adapting recent works linking Nesterov acceleration and Frank-Wolfe methods. We benchmark the proposed accelerated collision detection method on two datasets composed of strictly convex and non-strictly convex shapes. Our results show that our approach significantly reduces the number of iterations to solve collision detection problems compared to the state-of-the-art GJK algorithm, leading to up to two times faster computation times.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
20204 - Robotics and automatic control
Result continuities
Project
<a href="/en/project/EF15_003%2F0000468" target="_blank" >EF15_003/0000468: Intelligent Machine Perception</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
ROBOTICS: SCIENCE AND SYSTEM XVIII
ISBN
978-0-9923747-8-5
ISSN
2330-7668
e-ISSN
2330-765X
Number of pages
14
Pages from-to
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Publisher name
Robotics Science and Systems
Place of publication
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Event location
New York
Event date
Jun 27, 2022
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000827625700039