## Receding Horizon Control of Autonomous Aerial Vehicles

### John Bellingham, Arthur Richards, Jonathan How

Pages 3741 - 3746, American Controls Conference, May 2002.

This paper presents a new approach to trajectory optimization
for autonomous fixed-wing aerial vehicles performing large-scale maneuvers.
The main result is a planner which designs nearly minimum time planar trajectories
to a goal, constrained by no-fly zones and the vehicle's maximum speed and turning
rate. Mixed-Integer Linear Programming (MILP) is used for the optimization,
and is well suited to trajectory optimization because it can incorporate logical
constraints, such as no-fly zone avoidance, and continuous constraints, such
as aircraft dynamics. MILP is applied over a receding planning horizon to reduce
the computational effort of the planner and to incorporate feedback. In this
approach, MILP is used to plan short trajectories that extend towards the goal,
but do not necessarily reach it. The cost function accounts for decisions beyond
the planning horizon by estimating the time to reach the goal from the plan's
end point. This time is estimated by searching a graph representation of the
environment. This approach is shown to avoid entrapment behind obstacles, to
yield near-optimal performance when comparison with the minimum arrival time
found using a fixed horizon controller is possible, and to work consistently
on large trajectory optimization problems that are intractable for the fixed
horizon controller.

Download: Paper

Professor Jonathan
P. How

jhow@mit.edu

November 24, 2002