Path Planning Algorithm based on Arnold Cat Map for Surveillance UAVs
Keywords: Unmanned aerial vehicle, adversarial environment, chaotic path, 3D Arnold’s cat map, volume surveillance
AbstractDuring their task accomplishment, autonomous unmanned aerial vehicles are facing more and more threats coming from both ground and air. In such adversarial environments, with no a priori information about the threats, a flying robot in charge with surveilling a specified 3D sector must perform its tasks by evolving on misleading and unpredictable trajectories to cope with enemy entities. In our view, the chaotic dynamics can be the cornerstone in designing unpredictable paths for such missions, even though this solution was not exploited until now by researchers in the 3D context. This paper addresses the flight path-planning issue for surveilling a given volume in adversarial conditions by proposing a proficient approach that uses the chaotic behaviour exhibited by the 3D Arnold’s cat map. By knowing the exact location of the volume under surveillance before take-off, the flying robot will generate the successive chaotic waypoints only with onboard resources, in an efficient manner. The method is validated by simulation in a realistic scenario using a detailed Simulink model for the X-4 Flyer quadcopter.
How to Cite
Curiac, D.-I., & Volosencu, C. (2015). Path Planning Algorithm based on Arnold Cat Map for Surveillance UAVs. Defence Science Journal, 65(6), 483-488. https://doi.org/10.14429/dsj.65.8483
Electronics & Communication Systems
Copyright (c) 2016 Defence Science Journal
Where otherwise noted, the Articles on this site are licensed under Creative Commons License: CC Attribution-Noncommercial-No Derivative Works 2.5 India