MILP-based trajectory generation in Relative Velocity Coordinates

Mixed-integer linear programming (MILP) for trajectory generation of mobile robot suffers from nonlinear constraints due to complex obstacle contours and dynamic environment. In this paper, relative velocity coordinates (RVCs) are proposed for solving the target pursuit and multiple-obstacle avoidance (TPMOA) problem. In the proposed RVCs, nonlinear constraints can be inherently described as linear inequalities, which allow MILP to be utilized to find the optimal trajectory satisfying the linear inequalities. The complexity of obstacle contour does not increase the computational load of the proposed approach. Simulation results are presented in comparison with those of evolutionary algorithm (EA), showing significant improvement in a number of aspects.