Path Planning Of Small-scale Unmanned Helicopters Using Receding Horizon MILP

This thesis studies the trajectory planning for the small-scale unmanned helicopters andpresents several trajectory optimization algorithms based on Receding Horizon Control andMixed Integer Linear Programming(RHC-MILP). The algorithms are specially suitable for thecase that environment is unknown ahead of time and needs to explore online. The algorithms aretested and demonstrated by computer simulation with the mathematical programming languageAMPL and the powerful commercial optimization solver CPLEX. The simulation results showthat, for the trajectory planning of the vehicles in complicated environment, the algorithms areapplicable of computing optimal trajectories in real-time. The research fields in this thesis areas follows.Firstly, the thesis studies the trajectory planning for the vehicles ?ying in the city. Theobstacle-avoidance is discussed which the obstacles is 3-dimension buildings. The algorithmof trajectory planning based on RHC-MILP is presented. The obstacle-avoidance constraintscan be formulated as linear constraints by introducing logic variables combining continuousvariables. The dynamics of the vehicles is linearly approximated. The cost function is aboutminimal time or/and other performance index. Then trajectory optimization problem can be for-mulated as MILP forms. By solving the MILP and using receding horizon strategy, an optimaltrajectory from start to goal is planned online. The simulation result shows that the algorithmcan produce optimal trajectory in real time.Secondly, the thesis studies the trajectory planning for the vehicles ?ying in the moun-tainous region. The terrain-avoidance and terrain-following of vehicles are discussed. Thealgorithm of the trajectory planning based on RHC-MILP is presented. A novel method is usedthat combines triangulated irregular network(TIN) and MILP describing terrain-avoidance. Thecost function has an item about the altitude cost, a suitable weight could keep the trajectory ofthe vehicle follows the terrain. By taking receding horizon strategy, and only considering thelocal terrain within the planning horizon, the computing time is greatly reduced. The simulationbased on random terrain demonstrates the the real-timeness and validness of the algorithm.Thirdly, the thesis studies the trajectory planning of agile vehicles. The transition amonghover, cruise and other ?ight modes as well as maneuvers are modeled as an automata. Tra-jectory planning is viewed as a sequential decision process. The continuous decision variablesare associated with the optimization of the ?ight modes, while logic decision variables are as-sociated with mode-choosing, mode-transition and maneuver execution. The guidance decisionproblem can be formulated as the MILP form. Finally, this thesis studies the trajectory planning for multi-vehicle's cooperative ?ights.The algorithm of the trajectory planning based on DRHC-MILP is presented. The distributedalgorithm of the trajectory optimization for multi-vehicle ?eet breaks the optimization intosmaller subproblems. Each vehicle in the ?eet plans its trajectory by solving a reduced sizeoptimization problem online. Each trajectory planed by the single vehicle satisfies all con-strains of collision avoidances as well as terrain avoidances. The optimization subproblems canbe solved within a group in parallel.