E2Coop: Energy Efficient and Cooperative Obstacle Detection and Avoidance for UAV Swarms

Shuangyao Huang, Haibo Zhang, Zhiyi Huang

Research output: Chapter in Book or Report/Conference proceedingConference Proceedingpeer-review

2 Citations (Scopus)

Abstract

Energy efficiency is of critical importance to trajectory planning for UAV swarms in obstacle avoidance. In this paper, we present E2Coop, a new scheme designed to avoid collisions for UAV swarms by tightly coupling Artificial Potential Field (APF) with Particle Swarm Planning (PSO) based trajectory planning. In E2Coop, swarm members perform trajectory planning cooperatively to avoid collisions in an energy-efficient manner. E2Coop exploits the advantages of the active contour model in image processing for trajectory planning. Each swarm member plans its trajectories on the contours of the environment field to save energy and avoid collisions to obstacles. Swarm members that fall within the safeguard distance of each other plan their trajectories on different contours to avoid collisions with each other. Simulation results demonstrate that E2Coop can save energy up to 51% compared with two state-of-the-art schemes.

Original languageEnglish
Title of host publication31st International Conference on Automated Planning and Scheduling, ICAPS 2021
EditorsSusanne Biundo, Minh Do, Robert Goldman, Michael Katz, Qiang Yang, Hankz Hankui Zhuo
PublisherAssociation for the Advancement of Artificial Intelligence
Pages634-642
Number of pages9
ISBN (Electronic)9781713832317
DOIs
Publication statusPublished - 2021
Externally publishedYes
Event31st International Conference on Automated Planning and Scheduling, ICAPS 2021 - Guangzhou, Virtual, China
Duration: 2 Aug 202113 Aug 2021

Publication series

NameProceedings International Conference on Automated Planning and Scheduling, ICAPS
Volume2021-August
ISSN (Print)2334-0835
ISSN (Electronic)2334-0843

Conference

Conference31st International Conference on Automated Planning and Scheduling, ICAPS 2021
Country/TerritoryChina
CityGuangzhou, Virtual
Period2/08/2113/08/21

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