Authors: Xiaoliang Wang; Deshi Li
Addresses: School of Electronic Information, Wuhan University, Wuhan, Hubei, China ' School of Electronic Information, Wuhan University, Wuhan, Hubei, China
Abstract: This paper addresses the problem of path planning for Unmanned Aerial Vehicles (UAVs) in an unknown directional region. Paths are planned to maximise the amount of information from desired region while accounting for the trajectory length. In this paper, an exploration system is proposed for specific cases with shifting directions such as rivers and lakes. Taking account of data synchronisation errors, this method maximises the amount of information value and optimises the path length. Desired region is divided into grids based on required image resolution as well as time needed during the process. Analyses show that the real area and path length are closely related to the yaw angle of UAVs. The path planning issue is studied as an optimisation problem and has been solved by a modified depth-first search method. Monte-Carlo simulations are carried out to validate the effectiveness of the proposed algorithm, in which the UAV performs a task to track targets on a flowing river.
Keywords: unmanned aerial vehicles; multiple UAVs; cooperative observation; directional regions; maximum information count; path planning; unknown regions; rivers; lakes; target tracking; data synchronisation; synchronisation errors; information value; path length optimisation; image resolution; yaw angle; depth-first search; Monte Carlo simulation.
International Journal of Wireless and Mobile Computing, 2015 Vol.8 No.3, pp.285 - 293
Received: 17 Jul 2014
Accepted: 16 Sep 2014
Published online: 13 May 2015 *