Wilderness Search and Rescue ͑WiSAR͒ entails searching over large regions in often rugged remote areas. Because of the large regions and potentially limited mobility of ground searchers, WiSAR is an ideal application for using small ͑human-packable͒ unmanned aerial vehicles ͑UAVs͒ to provide aerial imagery of the search region. This paper presents a brief analysis of the WiSAR problem with emphasis on practical aspects of visual-based aerial search. As part of this analysis, we present and analyze a generalized contour search algorithm, and relate this search to existing coverage searches. Extending beyond laboratory analysis, lessons from field trials with search and rescue personnel indicated the immediate need to improve two aspects of UAV-enabled search: How video information is presented to searchers and how UAV technology is integrated into existing WiSAR teams. In response to the first need, three computer vision algorithms for improving video display presentation are compared; results indicate that constructing temporally localized image mosaics is more useful than stabilizing video imagery. In response to the second need, a goal-directed task analysis of the WiSAR domain was conducted and combined with field observations to identify operational paradigms and field tactics for coordinating the UAV operator, the payload operator, the mission manager, and ground searchers.

Abstract-Wilderness Search and Rescue can benefit from aerial imagery of the search area. Mini Unmanned Aerial Vehicles can potentially provide such imagery, provided that the autonomy, search algorithms, and operator control unit are designed to support coordinated human-robot search teams. Using results from formal analyses of the WiSAR problem domain, we summarize and discuss information flow requirements for WiSAR with an eye toward the efficient use of mUAVs to support search. We then identify and discuss three different operational paradigms for performing field searches, and identify influences that affect which human-robot team paradigm is best. Since the likely location of a missing person is key in determining the best paradigm given the circumstances, we report on preliminary efforts to model the behavior of missing persons in a given situation. Throughout the paper, we use information obtained from subject matter experts from Utah County Search and Rescue, and report experiences and "lessons learned" from a series of trials using human-robot teams to perform mock searches.

As multiple robot systems become more common, it is necessary to develop scalable human-robot interfaces that permit the inclusion of additional robots without reducing the overall system performance. Workload and situational awareness play key roles in determining the ratio of m operators to n robots. A scalable interface, where m is much smaller than n, will have to manage the operator's workload and promote a high level of situation awareness. This work focused on the development of a scalable interface for a single human-multiple robot system. This interface introduces a relational "halo" display that augments a camera view to promote situational awareness and the management of multiple robots by providing information regarding the robots' relative locations with respect to a selected robot. An evaluation was conducted to determine the scalability of the interface focusing on the effects of increasing the number of robots on workload, situation awareness, and robot usage. Twenty participants completed two bomb defusing tasks: one employing six robots, the other nine. The results indicated that increasing the number of robots increased overall workload and the operator's situation awareness.

Wilderness search and rescue (WiSAR) requires thousands of hours of search over large and complex terrains. Mini-UAVs (unmanned aerial vehicles) may dramatically improve WiSAR search efficiency. Early field trials in UAV-enabled WiSAR indicated a need to improve the human-UAV interaction, the coordination between the UAV and ground search resources, and the UAV technology. A cognitive task analysis was conducted to inform the design of the UAV technology, the associated interface, and the roles and responsibilities associated with effectively integrating the technology into the existing WiSAR response. Two cognitive task analysis techniques were employed: goal-directed task analysis and a partial cognitive work analysis that included a work domain analysis and a control task analysis. Early field trials and WiSAR search personnel informed the task analyses, which consequently informed the UAV technology design and integration. This paper (a) reviews how and why the task analyses were conducted, how the systems engineering process incorporated field trials to inform the task analyses and to guide the technology development; and (b) provides examples of how the analyses informed the resulting technology development with an eye toward providing insight into how such analysis techniques can be applied to developing UAV systems.

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