Mobile Robot Multi-Objective Trajectory Planning with Velocity obstacles

A velocity obstacle crossing the paths of Mobile robots is a general situation in both indoor and outdoor environments. Velocity obstacles reduce or alter the speed of the robot. The prediction of exact trajectory for the robot motion by the currently available methods is to be improved a lot. This gap is to be addressed. This manuscript proposes two multi-objective optimization methods based on evolutionary algorithms to bridge the gap. Evolutionary algorithms - Multi-objective Differential Evolution (MODE) and Elitist non-dominated sorting Genetic Algorithm (NSGA-II) are proposed in this paper. A car like mobile robot is designed, fabricated and experimented. Travel time and energy spent are considered as performance criteria in the problem solved by the proposed algorithms. Dynamic parameters' limitations, geometrical parameters' constraints and kinematic characteristics' bounds are considered in the problem. Both fixed and moving obstacles were present near the robot in its environment. So, motion of both obstacles was considered by the algorithms while planning the path of the robot. A third order NURBS function is used to characterize the mobile robot's trajectory. The optimal trajectory for the mobile robot was found by both NSGA-II and MODE. Experiments also conducted to validate the algorithms' results. Experimental validation proves that both NSGA-II and MODE are good algorithms to consider for optimal trajectory planning of mobile robots while considering stationary obstacles.