Based On The Rapid Expansion Of The Random Tree Robot Path Planning Algorithm Simulation Platform

Robotics is the science or study of the technology associated with the theory, design, fabrication and application of robots to autonomously complete work. Robots path planning plays an important role in Robotics.The Rapidly-Exploring Random Tree (RRT) is a search structure constructed incrementally in a way that quickly reduces the expected distance to nodes in the search structure, of randomly-chosen points in the search space. And it has recently shown promising results in trajectory design and path planning problems.This thesis presents two path planner based on the RRTs and has realized them.One of them is RRT planner. The soul of the design is the basic RRT algorithm and the simulative results show the nice properties of planner, such as 1) the expansion of an RRT is heavily biased toward unexplored portions of the state space; 2) the distribution of vertices in an RRT approaches the sampling distribution, leading to consistent behavior; 3) an RRT is probabilistically complete under very general conditions.The other one is RRT-Connect planner. The inspiration of design comes from RRT-Connect algorithm, a variation of RRT. And the simulative results show not only the same nice properties inherit from basic RRT, but also higher search speed and more efficiency.This thesis also presents and realize a simulative system based on RRT algorithm, whose developing process conform to UML standard. The system holds the functions such as configuring parameters, drawing map and showing the process of generating path real time. The simulative results show that the system run stably and can intuitively show the searching process.