Abstract

Wilderness Search and Rescue is the process of finding and assisting persons who are lost in remote wilderness areas. Because such areas are often rugged or relatively inaccessible, searching for missing persons can take huge amounts of time and resources. Camera-equipped mini-Unmanned Aerial Vehicles have the potential for speeding up the search process by enabling searchers to view aerial video of an area of interest while closely coordinating with nearby ground searchers. In this paper, we report on lessons learned by trying to use UAVs to support WiSAR. Our research methodology has relied heavily on field trials involving searches conducted under the direction of practicing search and rescue personnel but using simulated missing persons. Lessons from these field trials include the immediate importance of seeing things well in the video, the field need for defining and supporting various roles in the search team, role-specific needs like supporting systematic search by providing a visualization tool to represent the quality of the search, and the on-going need to better support interactions between ground and video searchers. Surprisingly to us, sophisticated autonomous search patterns were less critical than we anticipated, though advances in video enhancement and visualizing search progress, as well as ongoing work to model the likely location of a missing person, open up the possibility of closing the loop between UAV path-planning, search quality, and the likely location of a moving missing person. Keywords: Unmanned Aerial Vehicles, Wilderness Search and Rescue, Human–Robot Interaction, Human Factors, Field Robotics, Graphical User Interfaces