Surrogate Modeling of Optimal Control Based Collision Avoidance System for Multirotor Unmanned Aerial Vehicles

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F23%3APU149409" target="_blank" >RIV/00216305:26230/23:PU149409 - isvavai.cz</a>

Výsledek na webu

<a href="https://ieeexplore.ieee.org/document/10311265" target="_blank" >https://ieeexplore.ieee.org/document/10311265</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/DASC58513.2023.10311265" target="_blank" >10.1109/DASC58513.2023.10311265</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Surrogate Modeling of Optimal Control Based Collision Avoidance System for Multirotor Unmanned Aerial Vehicles

Popis výsledku v původním jazyce

A dynamically changing operating environment, along with constraints imposed through applicable safety requirements, pose significant challenges to autonomous multi-rotor manned and unmanned aerial vehicle operations in urban areas. Safety-critical onboard collision avoidance capability requires fast decision making accounting for uncertainties arising in complex environments. Successive convexification approach is applied to generate collision avoidance trajectories assuming both static and moving obstacles. The uncertainties arising in estimated state of moving obstacles are accounted for by construction of Polynomial Chaos Expansion based surrogate model. The obtained surrogate model can be evaluated in real-time to update the collision avoidance trajectory in case of change of tracked obstacle's state. The designed trajectories are subsequently tracked using a closed-loop Model Predictive Control scheme assuming a quadcopter configuration.

Název v anglickém jazyce

Surrogate Modeling of Optimal Control Based Collision Avoidance System for Multirotor Unmanned Aerial Vehicles

Popis výsledku anglicky

A dynamically changing operating environment, along with constraints imposed through applicable safety requirements, pose significant challenges to autonomous multi-rotor manned and unmanned aerial vehicle operations in urban areas. Safety-critical onboard collision avoidance capability requires fast decision making accounting for uncertainties arising in complex environments. Successive convexification approach is applied to generate collision avoidance trajectories assuming both static and moving obstacles. The uncertainties arising in estimated state of moving obstacles are accounted for by construction of Polynomial Chaos Expansion based surrogate model. The obtained surrogate model can be evaluated in real-time to update the collision avoidance trajectory in case of change of tracked obstacle's state. The designed trajectories are subsequently tracked using a closed-loop Model Predictive Control scheme assuming a quadcopter configuration.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2023

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

AIAA/IEEE Digital Avionics Systems Conference - Proceedings

ISBN

979-8-3503-3357-2

ISSN

2155-7195

e-ISSN

—

Počet stran výsledku

7

Strana od-do

1-7

Název nakladatele

Institute of Electrical and Electronics Engineers

Místo vydání

Barcelona

Místo konání akce

Barcelona

Datum konání akce

1. 10. 2023

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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