Image-Based Multi-UAV Tracking System in a Cluttered Environment
A tracking controller for unmanned aerial vehicles (UAVs) is developed to track moving targets undergoing unknown translational and rotational motions. The main challenges are to control both the relative positions and angles between the target and the UAVs to within desired values, and to guarantee...
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Veröffentlicht in: | IEEE transactions on control of network systems 2022-12, Vol.9 (4), p.1863-1874 |
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creator | Hung, Hsin-Ai Hsu, Hao-Huan Cheng, Teng-Hu |
description | A tracking controller for unmanned aerial vehicles (UAVs) is developed to track moving targets undergoing unknown translational and rotational motions. The main challenges are to control both the relative positions and angles between the target and the UAVs to within desired values, and to guarantee that the generated control inputs to the UAVs are feasible (i.e., within their motion capabilities). Moreover, the UAVs are controlled to ensure that the target always remains within the fields of view of their onboard cameras. To the best of our knowledge, this is the first work to apply multiple UAVs to cooperatively track a dynamic target while ensuring that the UAVs remain connected and that both occlusion and collisions are avoided. To achieve these control objectives, a designed controller solved based on the aforementioned tracking controller using quadratic programming can generate minimally invasive control actions to achieve occlusion avoidance and collision avoidance. Furthermore, control barrier functions (CBFs) with a distributed design are developed in order to reduce the amount of inter-UAV communication. Simulations were performed to assess the efficacy and performance of the developed CBF-based controller for the multi-UAV system in tracking a target. |
doi_str_mv | 10.1109/TCNS.2022.3181255 |
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The main challenges are to control both the relative positions and angles between the target and the UAVs to within desired values, and to guarantee that the generated control inputs to the UAVs are feasible (i.e., within their motion capabilities). Moreover, the UAVs are controlled to ensure that the target always remains within the fields of view of their onboard cameras. To the best of our knowledge, this is the first work to apply multiple UAVs to cooperatively track a dynamic target while ensuring that the UAVs remain connected and that both occlusion and collisions are avoided. To achieve these control objectives, a designed controller solved based on the aforementioned tracking controller using quadratic programming can generate minimally invasive control actions to achieve occlusion avoidance and collision avoidance. Furthermore, control barrier functions (CBFs) with a distributed design are developed in order to reduce the amount of inter-UAV communication. 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(IEEE) 2022</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c336t-be8b25f9376de0b8575f1fa777dd98dd8971eb83f5a38f915d223ba61180864b3</citedby><cites>FETCH-LOGICAL-c336t-be8b25f9376de0b8575f1fa777dd98dd8971eb83f5a38f915d223ba61180864b3</cites><orcidid>0000-0002-1451-3937 ; 0000-0001-9920-4457 ; 0000-0002-5307-7023</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/9792429$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,796,27924,27925,54758</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/9792429$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Hung, Hsin-Ai</creatorcontrib><creatorcontrib>Hsu, Hao-Huan</creatorcontrib><creatorcontrib>Cheng, Teng-Hu</creatorcontrib><title>Image-Based Multi-UAV Tracking System in a Cluttered Environment</title><title>IEEE transactions on control of network systems</title><addtitle>TCNS</addtitle><description>A tracking controller for unmanned aerial vehicles (UAVs) is developed to track moving targets undergoing unknown translational and rotational motions. The main challenges are to control both the relative positions and angles between the target and the UAVs to within desired values, and to guarantee that the generated control inputs to the UAVs are feasible (i.e., within their motion capabilities). Moreover, the UAVs are controlled to ensure that the target always remains within the fields of view of their onboard cameras. To the best of our knowledge, this is the first work to apply multiple UAVs to cooperatively track a dynamic target while ensuring that the UAVs remain connected and that both occlusion and collisions are avoided. To achieve these control objectives, a designed controller solved based on the aforementioned tracking controller using quadratic programming can generate minimally invasive control actions to achieve occlusion avoidance and collision avoidance. Furthermore, control barrier functions (CBFs) with a distributed design are developed in order to reduce the amount of inter-UAV communication. Simulations were performed to assess the efficacy and performance of the developed CBF-based controller for the multi-UAV system in tracking a target.</description><subject>Autonomous aerial vehicles</subject><subject>Cameras</subject><subject>Collision avoidance</subject><subject>Control systems design</subject><subject>Controllers</subject><subject>Estimation</subject><subject>Kalman filters</subject><subject>Maintenance engineering</subject><subject>Moving targets</subject><subject>Occlusion</subject><subject>Quadratic programming</subject><subject>Robot kinematics</subject><subject>Safety</subject><subject>Target tracking</subject><subject>Tracking control</subject><subject>tracking of moving targets</subject><subject>Tracking systems</subject><subject>UAV</subject><subject>Unmanned aerial vehicles</subject><subject>unscented Kalman filter</subject><subject>Visualization</subject><issn>2325-5870</issn><issn>2372-2533</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9kE1PAjEQhhujiQT5AcbLJp6L_aDb9iZuQElQD4DXpktnySK7i23XhH_vbiCeZg7P-07mQeiekjGlRD-ts4_VmBHGxpwqyoS4QgPGJcNMcH7d70xgoSS5RaMQ9oSQHlKSD9DzorI7wC82gEve20Ms8Wb6lay93X6X9S5ZnUKEKinrxCbZoY0RfAfO6t_SN3UFdbxDN4U9BBhd5hBt5rN19oaXn6-LbLrEW87TiHNQOROF5jJ1QHIlpChoYaWUzmnlnNKSQq54ISxXhabCMcZzm1KqiEonOR-ix3Pv0Tc_LYRo9k3r6-6kYVKk3TuTVHUUPVNb34TgoTBHX1bWnwwlpndlelemd2UurrrMwzlTAsA_r6VmE6b5H26BY0g</recordid><startdate>20221201</startdate><enddate>20221201</enddate><creator>Hung, Hsin-Ai</creator><creator>Hsu, Hao-Huan</creator><creator>Cheng, Teng-Hu</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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subjects | Autonomous aerial vehicles Cameras Collision avoidance Control systems design Controllers Estimation Kalman filters Maintenance engineering Moving targets Occlusion Quadratic programming Robot kinematics Safety Target tracking Tracking control tracking of moving targets Tracking systems UAV Unmanned aerial vehicles unscented Kalman filter Visualization |
title | Image-Based Multi-UAV Tracking System in a Cluttered Environment |
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