Optimal mobile robot path planning in the presence of moving obstacles

This paper presents an optimisation method to search for the optimal trajectory of an unmanned mobile robot while avoiding stationary and moving obstacles that may be in collision route. In order to meet the kinematic restrictions of the vehicle, the path is estimated using a finite-dimensional approximating space generated by B-splines basis functions. A penalised continuous functional is used to convert the constrained minimisation problem into an unconstrained one. The optimisation is performed through a genetic algorithm that searches the finite-dimensional space of the B-splines coefficients which determine the trajectory to be travelled. Experimental results with linear and nonlinear moving obstacle fields illustrate the estimated optimal trajectories.