Detail publikačního výsledku

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

NOVÁK, J.; CHUDÝ, P.

Originální název

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

Anglický název

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

Druh

Stať ve sborníku v databázi WoS či Scopus

Originální abstrakt

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.

Anglický abstrakt

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.

Klíčová slova

collision avoidance, polynomial chaos expansion,
multi-rotor vehicle, successive convexification

Klíčová slova v angličtině

collision avoidance, polynomial chaos expansion,
multi-rotor vehicle, successive convexification

Autoři

NOVÁK, J.; CHUDÝ, P.

Rok RIV

2024

Vydáno

28.10.2023

Nakladatel

Institute of Electrical and Electronics Engineers

Místo

Barcelona

ISBN

979-8-3503-3357-2

Kniha

AIAA/IEEE Digital Avionics Systems Conference - Proceedings

ISSN

2155-7195

Periodikum

IEEE/AIAA ... Digital Avionics Systems Conference

Číslo

10

Stát

Spojené státy americké

Strany od

1

Strany do

7

Strany počet

7

URL

https://ieeexplore.ieee.org/document/10311265

BibTex

@inproceedings{BUT185182,
  author="Jiří {Novák} and Peter {Chudý}",
  title="Surrogate Modeling of Optimal Control Based Collision Avoidance System for Multirotor Unmanned Aerial Vehicles",
  booktitle="AIAA/IEEE Digital Avionics Systems Conference - Proceedings",
  year="2023",
  journal="IEEE/AIAA ... Digital Avionics Systems Conference",
  number="10",
  pages="1--7",
  publisher="Institute of Electrical and Electronics Engineers",
  address="Barcelona",
  doi="10.1109/DASC58513.2023.10311265",
  isbn="979-8-3503-3357-2",
  issn="2155-7195",
  url="https://ieeexplore.ieee.org/document/10311265"
}