LSwarm: Efficient Collision Avoidance for Large Swarms with Coverage Constraints in Complex Urban Scenes

In this paper, we address the problem of collision avoidance for a swarm of UAVs used for continuous surveillance of an urban environment. Our method, LSwarm, efficiently avoids collisions with static obstacles, dynamic obstacles and other agents in 3-D urban environments while considering coverage...

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Bibliographic Details
Main Authors: Arul, Senthil Hariharan, Sathyamoorthy, Adarsh Jagan, Patel, Shivang, Otte, Michael, Xu, Huan, Lin, Ming C, Manocha, Dinesh
Format: Report
Language:unknown
Published: arXiv 2019
Subjects:
Robotics cs.RO
FOS Computer and information sciences
Orca
Online Access:https://dx.doi.org/10.48550/arxiv.1902.08379
https://arxiv.org/abs/1902.08379
id ftdatacite:10.48550/arxiv.1902.08379
record_format openpolar
spelling ftdatacite:10.48550/arxiv.1902.08379 2023-05-15T17:53:47+02:00 LSwarm: Efficient Collision Avoidance for Large Swarms with Coverage Constraints in Complex Urban Scenes Arul, Senthil Hariharan Sathyamoorthy, Adarsh Jagan Patel, Shivang Otte, Michael Xu, Huan Lin, Ming C Manocha, Dinesh 2019 https://dx.doi.org/10.48550/arxiv.1902.08379 https://arxiv.org/abs/1902.08379 unknown arXiv arXiv.org perpetual, non-exclusive license http://arxiv.org/licenses/nonexclusive-distrib/1.0/ Robotics cs.RO FOS Computer and information sciences Preprint Article article CreativeWork 2019 ftdatacite https://doi.org/10.48550/arxiv.1902.08379 2022-04-01T08:54:36Z In this paper, we address the problem of collision avoidance for a swarm of UAVs used for continuous surveillance of an urban environment. Our method, LSwarm, efficiently avoids collisions with static obstacles, dynamic obstacles and other agents in 3-D urban environments while considering coverage constraints. LSwarm computes collision avoiding velocities that (i) maximize the conformity of an agent to an optimal path given by a global coverage strategy and (ii) ensure sufficient resolution of the coverage data collected by each agent. Our algorithm is formulated based on ORCA (Optimal Reciprocal Collision Avoidance) and is scalable with respect to the size of the swarm. We evaluate the coverage performance of LSwarm in realistic simulations of a swarm of quadrotors in complex urban models. In practice, our approach can compute collision avoiding velocities for a swarm composed of tens to hundreds of agents in a few milliseconds on dense urban scenes consisting of tens of buildings. : 11 pages Report Orca DataCite Metadata Store (German National Library of Science and Technology)
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language unknown
topic Robotics cs.RO
FOS Computer and information sciences
spellingShingle Robotics cs.RO
FOS Computer and information sciences
Arul, Senthil Hariharan
Sathyamoorthy, Adarsh Jagan
Patel, Shivang
Otte, Michael
Xu, Huan
Lin, Ming C
Manocha, Dinesh
LSwarm: Efficient Collision Avoidance for Large Swarms with Coverage Constraints in Complex Urban Scenes
topic_facet Robotics cs.RO
FOS Computer and information sciences
description In this paper, we address the problem of collision avoidance for a swarm of UAVs used for continuous surveillance of an urban environment. Our method, LSwarm, efficiently avoids collisions with static obstacles, dynamic obstacles and other agents in 3-D urban environments while considering coverage constraints. LSwarm computes collision avoiding velocities that (i) maximize the conformity of an agent to an optimal path given by a global coverage strategy and (ii) ensure sufficient resolution of the coverage data collected by each agent. Our algorithm is formulated based on ORCA (Optimal Reciprocal Collision Avoidance) and is scalable with respect to the size of the swarm. We evaluate the coverage performance of LSwarm in realistic simulations of a swarm of quadrotors in complex urban models. In practice, our approach can compute collision avoiding velocities for a swarm composed of tens to hundreds of agents in a few milliseconds on dense urban scenes consisting of tens of buildings. : 11 pages
format Report
author Arul, Senthil Hariharan
Sathyamoorthy, Adarsh Jagan
Patel, Shivang
Otte, Michael
Xu, Huan
Lin, Ming C
Manocha, Dinesh
author_facet Arul, Senthil Hariharan
Sathyamoorthy, Adarsh Jagan
Patel, Shivang
Otte, Michael
Xu, Huan
Lin, Ming C
Manocha, Dinesh
author_sort Arul, Senthil Hariharan
title LSwarm: Efficient Collision Avoidance for Large Swarms with Coverage Constraints in Complex Urban Scenes
title_short LSwarm: Efficient Collision Avoidance for Large Swarms with Coverage Constraints in Complex Urban Scenes
title_full LSwarm: Efficient Collision Avoidance for Large Swarms with Coverage Constraints in Complex Urban Scenes
title_fullStr LSwarm: Efficient Collision Avoidance for Large Swarms with Coverage Constraints in Complex Urban Scenes
title_full_unstemmed LSwarm: Efficient Collision Avoidance for Large Swarms with Coverage Constraints in Complex Urban Scenes
title_sort lswarm: efficient collision avoidance for large swarms with coverage constraints in complex urban scenes
publisher arXiv
publishDate 2019
url https://dx.doi.org/10.48550/arxiv.1902.08379
https://arxiv.org/abs/1902.08379
genre Orca
genre_facet Orca
op_rights arXiv.org perpetual, non-exclusive license
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
op_doi https://doi.org/10.48550/arxiv.1902.08379
_version_ 1766161486451834880

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