A mode-switching path planner for UAV-assisted search and rescue
Allison D. Ryan, J. Karl Hedrick · 2006
Unmanned aerial vehicles (UAVs) can assist in U.S. Coast Guard maritime search and rescue missions by flying in formation with a manned helicopter while using infrared cameras to search the water for targets. Current search and rescue flight patterns contain abrupt turns that can be achieved by a helicopter but not by a fixed-wing UAV. Therefore, a necessity for UAV-assisted search and rescue is path planning and control that allows a UAV to track a helicopter performing such maneuvers while maintaining the desired sensor coverage and the safety of all aircraft. A feasible path planning algorithm combined with an off the shelf autopilot system is proposed. The path planning algorithm consists of four modes, each with an associated domain of application. Each mode is formulated to provide safety and contiguous sensor coverage between the UAV and the helicopter. For each of a series of k corners, the along-track distance between the vehicles is defined as L(k). By representing the path planner as a finite automaton, it is shown that any execution of the system causes the series {L(k)} to converge to zero, thereby resulting in satisfactory tracking. Simulations were performed with a non-linear UAV model and a commercial autopilot system in the control loop. In these simulations, the desired trajectories were commanded to the autopilot as a series of waypoints. However, the UAV was unable to accurately track the desired trajectories, resulting in oscillatory paths with unpredictable lengths.