Use of Unmanned Aerial Vehicles in Wilderness Search and Rescue Operations: A Scoping Review

Abstract

Wilderness Search and Rescue (WSAR) focuses on locating and extricating missing persons in remote settings. As unmanned aerial vehicle (UAV) or "drone" technology has evolved, so has the literature describing its application in WSAR operations. We conducted a scoping review of literature that describes the use of UAVs in WSAR contexts. The Joanna Briggs Institute Framework for scoping reviews was followed using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews method. Additional individual databases, article reference lists, and relevant grey literature were also included in the search to provide an impartial scope. Seven hundred forty-seven articles were identified. Of these, 56 were found to be duplicates. The remaining 691 were further screened and checked for eligibility. Ultimately, 21 studies were found that met our inclusion criteria. This literature supports the use of UAVs to increase the safety and efficiency of a WSAR operation for locating victims, assessing risks, carrying equipment, and restoring communication systems. Unmanned aerial vehicles are a potentially useful adjunct in the management of WSAR operations. Their limitations include objects obscuring victims, weather changes, uneven terrain, battery-limited flight time, and susceptibility to environmental damage.

Path planning for a UGV using Salp Swarm Algorithm

“…The dynamics of the autonomous navigation landscape change and the effectiveness and robustness of path planning algorithms are critical for the operational success of Unmanned Ground Vehicles (UGVs) [1][2][3][4][5][6][7][8][9][10][11][12]. These vehicles are used in various applications including military operations [13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30], disaster reliefs, as well as agricultural automation and require sophisticated navigation techniques that can allow them to navigate safely and effectively through difficult environments [31][32][33][34][35][36][37][38][39][40][41][42][43][44][45]. Traditional path planning methods mainly face an optimization task of path length and computational efficiency in dynamic and unpredictable terrains .…”