Adaptive dynamic path re-planning RRT algorithms with game theory for UAVs


Autoria(s): Bertola, Andrea; Gonzalez, Luis Felipe
Data(s)

25/02/2013

Resumo

The main aim of this paper is to describe an adaptive re-planning algorithm based on a RRT and Game Theory to produce an efficient collision free obstacle adaptive Mission Path Planner for Search and Rescue (SAR) missions. This will provide UAV autopilots and flight computers with the capability to autonomously avoid static obstacles and No Fly Zones (NFZs) through dynamic adaptive path replanning. The methods and algorithms produce optimal collision free paths and can be integrated on a decision aid tool and UAV autopilots.

Formato

application/pdf

Identificador

http://eprints.qut.edu.au/59093/

Relação

http://eprints.qut.edu.au/59093/1/Paper_68_Bertola_Gonzalez_.pdf

http://www.aiac15.com/

Bertola, Andrea & Gonzalez, Luis Felipe (2013) Adaptive dynamic path re-planning RRT algorithms with game theory for UAVs. In 15th Australian International Aerospace Congress (AIAC15), 25-28 February 2013, Melbourne Converntion Centre, Melbourne, VIC.

Direitos

Copyright 2013 [please consult the author]

Fonte

Australian Research Centre for Aerospace Automation; School of Electrical Engineering & Computer Science; Institute for Future Environments; Science & Engineering Faculty

Palavras-Chave #010303 Optimisation #050200 ENVIRONMENTAL SCIENCE AND MANAGEMENT #090100 AEROSPACE ENGINEERING #090104 Aircraft Performance and Flight Control Systems #Path planning #adaptive #UAV #UAS #replanning #Rapidly Exploring Random Trees #search and rescue #Matlab #Game theory #CEDM
Tipo

Conference Paper