TY - JOUR
T1 - A Novel Path-finding Approach for Maritime Search and Rescue Missions Incorporating Dynamic Probability of a target Location
AU - Larsen, Andreas Kühne
AU - Kilic, Kemal Ihsan
AU - Ladefoged, Magnus Berg
AU - Sung, Inkyung
PY - 2025
Y1 - 2025
N2 - Current practice for maritime search and rescue (MSAR) adheres to predetermined full-coverage patterns for finding targets. These do not account for key success factors for MSAR missions such as the dynamic location of targets, updates on situational awareness during mission execution, and search vehicle kinematics. Consequently, current practice cannot incorporate realistic MSAR operational conditions into path-finding, increasing the likelihood of mission failure. To address this issue, a novel, flexible path-finding framework is proposed for generating a path while dynamically updating the probability of a target based on the path's trajectories. The solution approach implements the A* algorithm, which can accommodate the dynamics of a vehicle and guarantees the optimality of the final path with respect to the target objective function. Experiments show that a more than 50% improvement in the time needed to guarantee a certain probability of finding a target is exhibited compared to the parallel sweep coverage path-finding approach.
AB - Current practice for maritime search and rescue (MSAR) adheres to predetermined full-coverage patterns for finding targets. These do not account for key success factors for MSAR missions such as the dynamic location of targets, updates on situational awareness during mission execution, and search vehicle kinematics. Consequently, current practice cannot incorporate realistic MSAR operational conditions into path-finding, increasing the likelihood of mission failure. To address this issue, a novel, flexible path-finding framework is proposed for generating a path while dynamically updating the probability of a target based on the path's trajectories. The solution approach implements the A* algorithm, which can accommodate the dynamics of a vehicle and guarantees the optimality of the final path with respect to the target objective function. Experiments show that a more than 50% improvement in the time needed to guarantee a certain probability of finding a target is exhibited compared to the parallel sweep coverage path-finding approach.
KW - A algorithm
KW - Optimization
KW - path-planning
KW - probability of containment
KW - search and rescue
UR - http://www.scopus.com/inward/record.url?scp=86000587092&partnerID=8YFLogxK
U2 - 10.1080/0305215X.2024.2446590
DO - 10.1080/0305215X.2024.2446590
M3 - Journal article
SN - 0305-215X
JO - Engineering Optimization
JF - Engineering Optimization
ER -