Providing coverage in multi-period searches: I've listed this as long term because searches that last longer than the median time (3 hr 10 min) are likely to cover larger areas. We need to improve communication and we need to learn how to stitch together multiple flights to cover larger areas with confidence. We'll almost certainly need better images to be really useful. Lanny's work on probabilistic search probably falls into this area since I anticipate that near-term use of the UAV would focus on a particular area rather than on an extended probability density function.

Modeling movement and probability of area: Although this is a research area dear to my heart, I think that it will probably only have impact in the long term. Three things must be addressed before it can have high impact. First, UAV's must be perceived as a useful tool by the search and rescue community. Second, we've got to get the models right so that they really help rather than just provide pretty pictures. Third, they have to complement emerging Geographic Information Systems intended to support the incident commander or the ground searcher.

Providing imagery in adverse weather or in extremely rugged terrain: If a search is a multi-period search, then it will be more likely that manned aircraft will be used to help the search. Unless we approach the same reliability as the manned aerial searches at a much cheaper price, it seems unlikely that the UAV technology will be used. Instead, we might want to find ways to provide aerial imagery in situations where it is impossible or dangerous to use manned aircraft. Better communications and more robust flight path planning would be essential in such circumstances.

Providing IR imagery at night: Many searches stop or are dramatically scaled back at night. If we could fly reliably enough, then we could gather IR imagery at night that, when combined with visible-spectrum imagery from the daytime, could help focus search in the right areas (or at least minimize the commitment of ground searchers to unlikely regions).

Enhancing probability of detection using image enhancement techniques: In challenging search areas, it would be very useful to enhance imagery to make man-made objects stand-out against the background. Since false alarms and missed detections dramatically affect the potential benefit of such technology, it is important that image enhancement be carefully studied.

New idea 6/4/09 Automatic identification of trail-based probability of areas:“ Assigning probabilities to the likely location of a missing person is a challenging task. A relatively new approach to assigning such probabilities is called “trail-based probability” ://www.sarinfo.bc.ca/Trailpoa.htm. This technique assumes that the missing person intends to follow a trail or other linear feature, but departs from this linear feature at some decision point. Decision points are supposed to be identified by ground searchers traversing the trail. Would it be possible to do this more quickly by having the UAV follow the trail, gathering imagery as it spirals over the waypoints delineating the trail, and automatically identifying possible decision points using computer vision techniques. These decision points could then be served as points of importance into a probabilistic model for how the missing person moves through the terrain.

New idea 6/12/09 Use UAVs with vertical flight/hovering capabilities: BYU has been doing significant work on two other kinds of UAVs that would greatly assist current UAV search methods: tail-sitter and quad-rotor UAVs. These could be used to safely fly much closer to the ground to get a better look at something that the main UAV has seen before a ground team is sent to investigate. It would also be a much better platform for guiding ground searchers through terrain or to a specific destination. We could look into both BYU's prototypes and at any commercially available platforms. –Mike Roscheck