Analysis of the Effect of Time Delay for Unmanned Aerial Vehicles with Applications to Vision Based Navigation
In this paper, we analyze the effect of time delay dynamics on controller design for Unmanned Aerial Vehicles (UAVs) with vision based navigation. Time delay is an inevitable phenomenon in cyber-physical systems, and has important implications on controller design and trajectory generation for UAVs....
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creator | Humais, Muhammad Ahmed Chehadeh, Mohamad Boiko, Igor Zweiri, Yahya |
description | In this paper, we analyze the effect of time delay dynamics on controller
design for Unmanned Aerial Vehicles (UAVs) with vision based navigation. Time
delay is an inevitable phenomenon in cyber-physical systems, and has important
implications on controller design and trajectory generation for UAVs. The
impact of time delay on UAV dynamics increases with the use of the slower
vision based navigation stack. We show that the existing models in the
literature, which exclude time delay, are unsuitable for controller tuning
since a trivial solution for minimizing an error cost functional always exists.
The trivial solution that we identify suggests use of infinite controller gains
to achieve optimal performance, which contradicts practical findings. We avoid
such shortcomings by introducing a novel nonlinear time delay model for UAVs,
and then obtain a set of linear decoupled models corresponding to each of the
UAV control loops. The cost functional of the linearized time delay model of
angular and altitude dynamics is analyzed, and in contrast to the delay-free
models, we show the existence of finite optimal controller parameters. Due to
the use of time delay models, we experimentally show that the proposed model
accurately represents system stability limits. Due to time delay consideration,
we achieved a tracking results of RMSE 5.01 cm when tracking a lemniscate
trajectory with a peak velocity of 2.09 m/s using visual odometry (VO) based
UAV navigation, which is on par with the state-of-the-art. |
doi_str_mv | 10.48550/arxiv.2209.01933 |
format | Article |
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design for Unmanned Aerial Vehicles (UAVs) with vision based navigation. Time
delay is an inevitable phenomenon in cyber-physical systems, and has important
implications on controller design and trajectory generation for UAVs. The
impact of time delay on UAV dynamics increases with the use of the slower
vision based navigation stack. We show that the existing models in the
literature, which exclude time delay, are unsuitable for controller tuning
since a trivial solution for minimizing an error cost functional always exists.
The trivial solution that we identify suggests use of infinite controller gains
to achieve optimal performance, which contradicts practical findings. We avoid
such shortcomings by introducing a novel nonlinear time delay model for UAVs,
and then obtain a set of linear decoupled models corresponding to each of the
UAV control loops. The cost functional of the linearized time delay model of
angular and altitude dynamics is analyzed, and in contrast to the delay-free
models, we show the existence of finite optimal controller parameters. Due to
the use of time delay models, we experimentally show that the proposed model
accurately represents system stability limits. Due to time delay consideration,
we achieved a tracking results of RMSE 5.01 cm when tracking a lemniscate
trajectory with a peak velocity of 2.09 m/s using visual odometry (VO) based
UAV navigation, which is on par with the state-of-the-art.</description><identifier>DOI: 10.48550/arxiv.2209.01933</identifier><language>eng</language><subject>Computer Science - Robotics ; Computer Science - Systems and Control</subject><creationdate>2022-09</creationdate><rights>http://arxiv.org/licenses/nonexclusive-distrib/1.0</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>228,230,780,885</link.rule.ids><linktorsrc>$$Uhttps://arxiv.org/abs/2209.01933$$EView_record_in_Cornell_University$$FView_record_in_$$GCornell_University$$Hfree_for_read</linktorsrc><backlink>$$Uhttps://doi.org/10.48550/arXiv.2209.01933$$DView paper in arXiv$$Hfree_for_read</backlink></links><search><creatorcontrib>Humais, Muhammad Ahmed</creatorcontrib><creatorcontrib>Chehadeh, Mohamad</creatorcontrib><creatorcontrib>Boiko, Igor</creatorcontrib><creatorcontrib>Zweiri, Yahya</creatorcontrib><title>Analysis of the Effect of Time Delay for Unmanned Aerial Vehicles with Applications to Vision Based Navigation</title><description>In this paper, we analyze the effect of time delay dynamics on controller
design for Unmanned Aerial Vehicles (UAVs) with vision based navigation. Time
delay is an inevitable phenomenon in cyber-physical systems, and has important
implications on controller design and trajectory generation for UAVs. The
impact of time delay on UAV dynamics increases with the use of the slower
vision based navigation stack. We show that the existing models in the
literature, which exclude time delay, are unsuitable for controller tuning
since a trivial solution for minimizing an error cost functional always exists.
The trivial solution that we identify suggests use of infinite controller gains
to achieve optimal performance, which contradicts practical findings. We avoid
such shortcomings by introducing a novel nonlinear time delay model for UAVs,
and then obtain a set of linear decoupled models corresponding to each of the
UAV control loops. The cost functional of the linearized time delay model of
angular and altitude dynamics is analyzed, and in contrast to the delay-free
models, we show the existence of finite optimal controller parameters. Due to
the use of time delay models, we experimentally show that the proposed model
accurately represents system stability limits. Due to time delay consideration,
we achieved a tracking results of RMSE 5.01 cm when tracking a lemniscate
trajectory with a peak velocity of 2.09 m/s using visual odometry (VO) based
UAV navigation, which is on par with the state-of-the-art.</description><subject>Computer Science - Robotics</subject><subject>Computer Science - Systems and Control</subject><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>GOX</sourceid><recordid>eNotj09PhDAUxLl4MKsfwJPvC4APCi094rr-STZ6wb2SR2mlCRRCySrfXhY9zUwmM8kvCO5ijNI8y_CBph97jpIEZYSxZOw6cIWjbvHWw2BgbjUcjNFqvqTS9hqedEcLmGGCT9eTc7qBQk-WOjjp1qpOe_i2cwvFOHZW0WwH52Ee4GT9auGR_Lp4p7P92rqb4MpQ5_Xtv-6C8vlQ7l_D48fL2744hsQFCxWrsRFcNiiMpjhDEWMS8zpdW8xTbjRKldYchUiJ5Rk3iLLJVM3J1JInbBfc_91uwNU42Z6mpbqAVxs4-wVCz1NA</recordid><startdate>20220905</startdate><enddate>20220905</enddate><creator>Humais, Muhammad Ahmed</creator><creator>Chehadeh, Mohamad</creator><creator>Boiko, Igor</creator><creator>Zweiri, Yahya</creator><scope>AKY</scope><scope>GOX</scope></search><sort><creationdate>20220905</creationdate><title>Analysis of the Effect of Time Delay for Unmanned Aerial Vehicles with Applications to Vision Based Navigation</title><author>Humais, Muhammad Ahmed ; Chehadeh, Mohamad ; Boiko, Igor ; Zweiri, Yahya</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a673-c3b0d769d07fea150710216b4a670846fe09c4b60774a3856f009d5cb6afb9623</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Computer Science - Robotics</topic><topic>Computer Science - Systems and Control</topic><toplevel>online_resources</toplevel><creatorcontrib>Humais, Muhammad Ahmed</creatorcontrib><creatorcontrib>Chehadeh, Mohamad</creatorcontrib><creatorcontrib>Boiko, Igor</creatorcontrib><creatorcontrib>Zweiri, Yahya</creatorcontrib><collection>arXiv Computer Science</collection><collection>arXiv.org</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Humais, Muhammad Ahmed</au><au>Chehadeh, Mohamad</au><au>Boiko, Igor</au><au>Zweiri, Yahya</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Analysis of the Effect of Time Delay for Unmanned Aerial Vehicles with Applications to Vision Based Navigation</atitle><date>2022-09-05</date><risdate>2022</risdate><abstract>In this paper, we analyze the effect of time delay dynamics on controller
design for Unmanned Aerial Vehicles (UAVs) with vision based navigation. Time
delay is an inevitable phenomenon in cyber-physical systems, and has important
implications on controller design and trajectory generation for UAVs. The
impact of time delay on UAV dynamics increases with the use of the slower
vision based navigation stack. We show that the existing models in the
literature, which exclude time delay, are unsuitable for controller tuning
since a trivial solution for minimizing an error cost functional always exists.
The trivial solution that we identify suggests use of infinite controller gains
to achieve optimal performance, which contradicts practical findings. We avoid
such shortcomings by introducing a novel nonlinear time delay model for UAVs,
and then obtain a set of linear decoupled models corresponding to each of the
UAV control loops. The cost functional of the linearized time delay model of
angular and altitude dynamics is analyzed, and in contrast to the delay-free
models, we show the existence of finite optimal controller parameters. Due to
the use of time delay models, we experimentally show that the proposed model
accurately represents system stability limits. Due to time delay consideration,
we achieved a tracking results of RMSE 5.01 cm when tracking a lemniscate
trajectory with a peak velocity of 2.09 m/s using visual odometry (VO) based
UAV navigation, which is on par with the state-of-the-art.</abstract><doi>10.48550/arxiv.2209.01933</doi><oa>free_for_read</oa></addata></record> |
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subjects | Computer Science - Robotics Computer Science - Systems and Control |
title | Analysis of the Effect of Time Delay for Unmanned Aerial Vehicles with Applications to Vision Based Navigation |
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