TY  - CONF
Y1  - 2012///
SN  - 9781467318716
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84876065766&doi=10.1109%2fICARCV.2012.6485293&partnerID=40&md5=7ac49f5cb8371641567fefe19028855f
A1  - Pierre, D.M.
A1  - Zakaria, N.
A1  - Pal, A.J.
EP  - 1000
CY  - Guangzhou
AV  - none
N2  - The demand for Unmanned Aerial Vehicle (UAV) extends to various civil and military missions. While the use of remotely controlled UAV reduces the rate of human casualties in hazardous environments, it is reported that most of UAV accidents are caused by human factor errors. Automated path planning is required and because of the multi-objective nature of UAV's missions, several heuristic approaches to path planning have been proposed in order to automate UAV's navigation. While solving multi-objective problems requires the search for a set of pareto-optimal points, it requires the involvement of the user to select the desired result from the solution space. In this paper, we propose a variant of Self-Organizing Map approach to finding a compromised solution for a multi-objective path planning problem that does not require user involvement. Preliminary tests conducted in virtual environments have shown the immunity of our algorithm to local minima, and its efficiency to respond to multiple objectives. © 2012 IEEE.
N1  - cited By 5; Conference of 2012 12th International Conference on Control, Automation, Robotics and Vision, ICARCV 2012 ; Conference Date: 5 December 2012 Through 7 December 2012; Conference Code:96538
KW  - Compromised solution; Contrasting Objectives; Hazardous environment; Key words; Multi objective; Multi-objective problem; Path planning problems; Path-planning
KW  -  Conformal mapping; Heuristic methods; Multiobjective optimization; Robotics; Robots; Unmanned aerial vehicles (UAV); Virtual reality
KW  -  Motion planning
TI  - Self-Organizing Map approach to determining compromised solutions for multi-objective UAV path planning
SP  - 995
ID  - scholars2466
ER  -