Rotation and translation selective Pareto optimal solution to the box-pushing problem by mobile robots using NSGA-II

Abstract

The paper proposes a novel formulation of the classical box-pushing problem by mobile robots as a multi-objective optimization problem, and presents Pareto optimal solution to the problem using non-dominated sorting genetic algorithm-II (NSGA-II). The proposed method adopts local planning scheme, and allows both turning and translation of the box in the robots' workspace in order to minimize the consumption of both energy and time. The planning scheme introduced here determines the magnitude of the forces applied by two mobile robots at specific location on the box in order to align and translate it along the time- and energy- optimal trajectory in each distinct step of motion of the box. The merit of the proposed work lies in autonomous selection of translation distance and other important parameters of the robot motion model using NSGA-II. The suggested scheme, to the best of the authors' knowledge, is a first successful realization of a communication-free, centralized cooperation between two robots used in box shifting problem satisfying both time and energy minimization objectives simultaneously, presuming no additional user-defined constraint on the selection of linear distance traversal.