Search for targets in a risky environment using multi‐objective optimisation. Issue 1 (1st January 2019)

• Record Type: Journal Article
• Authors: Angley, Daniel; Ristic, Branko; Moran, William; Himed, Braham
• Is Part Of: IET radar, sonar & navigation. Volume 13:Issue 1(2019)
• Page Start: 123
• Page End: 127
• Publication Date: 2019-01-01
• Subjects: mobile robots -- path planning -- entropy -- remotely operated vehicles -- autonomous aerial vehicles -- optimisation; risky environment -- multiobjective optimisation -- online unmanned aerial vehicle path‐planning strategy -- UAV -- autonomous search -- reward -- convex combinations -- extreme case -- pure search -- systematic search pattern -- survival objective; Signal processing -- Periodicals; Radar -- Periodicals; Sonar -- Periodicals; Electronics in navigation -- Periodicals; Navigation -- Periodicals; 621.3848
• DOI: 10.1049/iet-rsn.2018.5184
• Languages: English
• ISSNs: 1751-8784

Abstract

Abstract : This study develops an online unmanned aerial vehicle (UAV) path‐planning strategy for autonomous search and localisation of targets in a risky environment that simultaneously optimises two objectives: (i) search and (ii) survival. The authors formulate two rewards (objective) functions corresponding to the two objectives and compute the Pareto front, formed by taking convex combinations of these rewards. In the extreme case of pure search, using entropy reduction as the reward, the trajectory of the UAV is reminiscent of a systematic search pattern. When combined with the survival objective, the search pattern appears more random, as the UAV intelligently trades off the reward of finding targets with the risk of being destroyed.