Optimal path planning for SUAS waypoint following in urban environments

In this research, Small Unmanned Aircraft Systems (SUAS) are used to determine feasible flight paths to multiple waypoints within an urban environment. Direct orthogonal collocation methods are used while leveraging navigation mesh techniques developed for fast geometric path planning solutions. Waypoints are included throughout a constrained city map to illustrate feasible flight paths through tightly constrained path corridors. The two-dimensional solution is achieved with a multi-phase approach defined through a discretized simplex mesh with aircraft control on acceleration and the change in the vehicle's heading rate. Constrained optimal control problems for SUAS have long suffered from excessive computation times caused by a combination of constraint modeling techniques and the quality of the initial path solution provided to the optimal control solver, ultimately preventing implementation into real-time, on-board systems. These issues are addressed herein with a new approach by triangulating the search space to define a polygonal search corridor free of constraints while alleviating the dependency of problem specific parameters by translating the problem to barycentric coordinates. Utilizing algorithms developed for geometric path planning, the initial path solution is comprised of four path intervals connected at each waypoint. These path intervals provide a constraint free search corridor defining a search domain for the optimal control software. Results are applied to illustrate two-dimensional flight trajectories through downtown Chicago at an altitude of 550 feet Above Ground Level (AGL). Computation and objective times are reported to illustrate the design implications for real-time optimal control systems.