This study explores a collision avoidance method for an unmanned ground vehicle (UGV). To develop the method, model predictive control framework is employed. With the philosophy of the model predictive control, the collision avoidance problem is formu...
This study explores a collision avoidance method for an unmanned ground vehicle (UGV). To develop the method, model predictive control framework is employed. With the philosophy of the model predictive control, the collision avoidance problem is formulated as a finite horizon optimal control problem. The solution of the collision avoidance problem is defined as path set the UGV follows and obtained by a particle swarm optimization (PSO) method. In addition, the model predictive path planning method for the collision avoidance is incorporated with the passivity constraint to assure the convergence of the UGV to a given goal point even during the collision avoidance maneuvering. To validate the performance of the proposed method, several experiments are conducted and the results are analyzed.