Toward More Efficient Methods for Path Planning of Mobile Robots: Simplified Non-Convex Constraints

In this paper the path planning of robots is formulated in the context of an optimization framework. It is shown that generating motion trajectories for mobile robots in real environment is cast into a non-convex problem. Global optimization techniques in the non-convex framework are thus exploited to obtain the desired trajectories. The approach presented in this paper can easily take the robot speed limitations into consideration and hence is more effective than other wellknown existing techniques. Simulation results are presented to demonstrate how robot trajectories are obtained. It is found that using the proposed methodology herein results in more realistic solutions for mobile robots path planning. Trajectory generation using optimization with non-convex constraints is an important move forward toward efficient path planning algorithms. Thus, results of this paper are of great significant especially in real experiments.