Optimal path planning using psychological profiling in drone‐assisted missing person search

• Published in: Advanced control for applications Vol. 5; no. 4
• Main Authors: Ewers, Jan‐Hendrik, Anderson, David, Thomson, Douglas
• Format: Journal Article
• Language: English
• Published: 01.12.2023
• Subjects: optimization; search and rescue; UAV
• ISSN: 2578-0727; 2578-0727
• DOI: 10.1002/adc2.167

Search and rescue operations are all time‐sensitive and this is especially true when searching for a vulnerable missing person, such as a child or elderly person suffering dementia. Recently, Police Scotland Air Support Unit has begun the deployment of drones to assist in missing person searches with success, although the efficacy of the search relies upon the expertise of the drone operator. In this paper, several algorithms for planning the search path are compared to determine which approach has the highest probability of finding the missing person in the shortest time. In addition to this, the use of á priori psychological profile information of the subject to create a probability map of likely locations within the search area was explored. This map is then used within a nonlinear optimization to determine the optimal flight path for a given search area and subject profile. Two optimization solvers were compared; genetic algorithms, and particle swarm optimization. Finally, the most effective algorithm was used to create a coverage path for a real‐life location, for which Police Scotland Air Support Unit completed multiple test flights. The generated flight paths based on the predicted intent of the lost person were found to perform statistically better than those of the expert police operators. Police Scotland Air Support Unit now employs drones in search and rescue operations for vulnerable missing individuals. This study evaluates multiple algorithms for planning search paths and explores the use of psychological profiles to create probability maps for likely locations within the search area. The research concludes that the automated optimization methods, specifically genetic algorithms and particle swarm optimization, outperform expert police operators in creating efficient flight paths to locate missing persons.