Genetic Algorithm Based Optimization Technique for Route Planning Of Wheeled Mobile Robot

In recent years, the significant uplift in artificial intelligence and other related electrical and mechanical integration technology made the robots to play an important role in modern life. In the study of mobile robot, trajectory planning has always been an important issue. With the presence of obstacles in the work environment, the best principles of finding the right path with obstacle avoidance method as a basis for moving the mobile robot from the starting point to the end point. In most studies, these principles are often optimized for the shortest or safest path chosen with least time-consuming, thus resulting in planning the route. Smooth path is extremely important for the navigation of the mobile robot. It avoids the process of moving tire slippage caused serious error location of conjecture. Further, the structure of the robot operation is indispensable due to limitations caused by the smoothness of the path of the carrier class of models. Therefore, this proposed algorithm studied and combined the genetic optimization technique with B Spline to provide the mobile robot to plan the route globally in a static environment.