Dubin’s Curve of RRT* Merged With A*

Abstract

One of the fundamental problems in mobile robotics is a robot path planning of the mobile robot through its environment. Path planning problem for the mobile robot with differential constraints using modified RRT (Rapidly exploring random tree) algorithm based on Dubin’s curves. the planning problem is considered as a problem of finding a feasible path between the initial and goal point in a static environment with obstacles. This process can be conducted either using local information from sensors or by emloying global a-priori known information about robot’s environment. The problem is how to generate a path from the beginning to the destination point gradually during movement using modified RRT (Rapidly exploring random tree) algorithm based on Dubin’s curves. Combining the dubin curve RRT* algorithm with A* is a new method that can calculate the entire path from the starting point of the destination before moving using global information about the map. The purpose of making the path is to make it easier for the operator to determine the path that must be traversed by the robot. The way the robot works is to read the line made by the operator using matlab based on the map, then matlab will calculate the distance of the path to be traversed using an algorithm from the star point to the goal point. Based on the simulation results that have been carried out this method is more efficient when compared to the RRT* or A* algorithms. because this algorithm can produce a path with the shortest path with a fast time to get to the destination point without crashing into obstacles. By adding a new algorithm to find a new path optimally to get a path that is close to optimal by combining and adjusting several feasible paths and also adding a searching-based algorithm, namely A* combined with Dubin Curve- RRT* is sampling based, where the A* algorithm has a function heuristic used to increase the cost and time of searching.