The paper discusses a novel path-planning strategy for autonomous multirobot coordination in wilderness search and rescue scenarios. The authors identify three key components: planning initial paths, implementing and evaluating paths, and replanning if necessary. They propose using "iso-probability curves" to create boundaries for robot paths, which are based on rays from the last known position of the lost subject. This method aims to improve systematic coverage of the search area, despite the challenges of unpredictable terrain and moving targets. The proposal is seen as an effective model for robot path planning in wilderness search and rescue efforts.The paper discusses a novel path-planning strategy for autonomous multirobot coordination in wilderness search and rescue scenarios. The authors identify three key components: planning initial paths, implementing and evaluating paths, and replanning if necessary. They propose using "iso-probability curves" to create boundaries for robot paths, which are based on rays from the last known position of the lost subject. This method aims to improve systematic coverage of the search area, despite the challenges of unpredictable terrain and moving targets. The proposal is seen as an effective model for robot path planning in wilderness search and rescue efforts.