Real Time Trajectory Planning for UAVs Using MILP

A probabilistic finite receding horizon approach for trajectory planning of autonomous air vehicles is presented. The approach is based on mixed integer linear programming (MILP) techniques. The risk areas are modelled by dynamic boundaries to direct the vehicle towards the target. Various constraints are formulated to avoid radar zones and collisions, etc. These constraints are extended to be both hard and soft so as to alleviate the infeasibility problem usually encountered. The finite receding horizon approach is numerically stable and can be applied to centralized trajectory planning of a fleet of UAVs in real time. The MILP problem is solved using commercially available software AMPL/CPLEX. Finally the approach is applied to different scenarios with upper and lower bounds on the speed and acceleration of each UAV.