title: Target-motion prediction for robotic search and rescue in wilderness environments.
abstract: This paper presents a novel modular methodology for predicting a lost person's (motion) behavior for autonomous coordinated multirobot wilderness search and rescue. The new concept of isoprobability curves is introduced and developed, which represents a unique mechanism for identifying the target's probable location at any given time within the search area while accounting for influences such as terrain topology, target physiology and psychology, clues found, etc. The isoprobability curves are propagated over time and space. The significant tangible benefit of the proposed target-motion prediction methodology is demonstrated through a comparison to a nonprobabilistic approach, as well as through a simulated realistic wilderness search scenario.
authors.affiliation: Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, ON, Canada. a.macwan@utoronto.ca
authors.forename: Ashish
authors.initials: A
authors.lastname: Macwan
authors.forename: Goldie
authors.initials: G
authors.lastname: Nejat
authors.forename: Beno
authors.initials: B
authors.lastname: Benhabib
mesh_terms: D002675:Child, Preschool; D003198:Computer Simulation; D003491:Cybernetics; D006801:Humans; D008954:Models, Biological; D009043:Motor Activity / Q000502:physiology*; D018635:Rescue Work / Q000379:methods*; D012371:Robotics / Q000295:instrumentation*; D055814:Wilderness