Extending RRT for Robot Motion Planning with SLAM

In this paper,the motion planning problem for mobile robot is addressed. Motion planning (MP) has diversified over the past few decades to include many different approaches such as cell decomposition, road maps, potential fields, and genetic algorithms. Often the goal of motion planning is not just obstacle avoidance but optimization of certain parameters as well. A motion planning algorithms based on Rapidly-exploring random Tree(RRT) is present in the paper. Then the RRT algorithm has been extended which combines the SLAM algorithm.The Extend-RRT-SLAM has been simulated in MobileSim.Simulation results show Extend-RRT-SLAM to be very effective for robot motion planning.