The Journal of Korea Robotics Society (로봇학회논문지)

Korea Robotics Society (한국로봇학회)
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Path Planning for Search and Surveillance of Multiple Unmanned Aerial Vehicles

다중 무인 항공기 이용 감시 및 탐색 경로 계획 생성

  • Sanha Lee (Department of Mechanical Engineering, Ulsan National Institute of Science and Technology) ;
  • Wonmo Chung (Department of Mechanical Engineering, Ulsan National Institute of Science and Technology) ;
  • Myunggun Kim (Department of Mechanical Engineering, Ulsan National Institute of Science and Technology) ;
  • Sang-Pill Lee (LIG NEX1) ;
  • Choong-Hee Lee (LIG NEX1) ;
  • Shingu Kim (LIG NEX1) ;
  • Hungsun Son (Department of Mechanical Engineering, Ulsan National Institute of Science and Technology)
  • Received : 2022.09.02
  • Accepted : 2022.11.14
  • Published : 2023.02.28
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Abstract

This paper presents an optimal path planning strategy for aerial searching and surveying of a user-designated area using multiple Unmanned Aerial Vehicles (UAVs). The method is designed to deal with a single unseparated polygonal area, regardless of polygonal convexity. By defining the search area into a set of grids, the algorithm enables UAVs to completely search without leaving unsearched space. The presented strategy consists of two main algorithmic steps: cellular decomposition and path planning stages. The cellular decomposition method divides the area to designate a conflict-free subsearch-space to an individual UAV, while accounting the assigned flight velocity, take-off and landing positions. Then, the path planning strategy forms paths based on every point located in end of each grid row. The first waypoint is chosen as the closest point from the vehicle-starting position, and it recursively updates the nearest endpoint set to generate the shortest path. The path planning policy produces four path candidates by alternating the starting point (left or right edge), and the travel direction (vertical or horizontal). The optimal-selection policy is enforced to maximize the search efficiency, which is time dependent; the policy imposes the total path-length and turning number criteria per candidate. The results demonstrate that the proposed cellular decomposition method improves the search-time efficiency. In addition, the candidate selection enhances the algorithmic efficacy toward further mission time-duration reduction. The method shows robustness against both convex and non-convex shaped search area.

Keywords

Acknowledgement

This project was funded by LIG NEX1 (UC190053ID, 2.200913) under Data link and Ground Control Software Standardization for Small UAVs

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