Research On Path Planning Algorithm Of Inspection Robot For High-speed Railway Terminals

With the growing popularity of intelligent mobile robots,the application of inspection robots in public places has become a hot research direction nowadays.Inspection robots have been widely used in substation,warehouse and other scenarios,but still have great development space in complex environment such as high-speed railway terminals.In this paper,considering the high-speed railway terminals environment and the inspection task of the robot,it is determined that the Rapidly-explorating Random Tree(RRT)algorithm and Artificial Potential Field(APF)are used as the research basis.In view of the existing shortcomings of the algorithm,the algorithms are improved respectively and a hybrid algorithm is proposed,and the feasibility of the hybrid algorithm is demonstrated by the Robot Operating System(ROS).The key work of this paper is as follows:(1)In order to solve the problems of slow convergence and low security of planned nodes in the traditional RRT algorithm,an RRT-connect algorithm based on safe distance expansion and intermediate node generation are proposed in the global path planning part.In this algorithm,the nodes that are too close to obstacles are removed by the screening mechanism,and the safe extension nodes are obtained,thus improving the safety of the planned path.Then,an intermediate node strategy is adopted to randomly generate intermediate nodes in the intermediate node region to improve the convergence speed of the algorithm.In this paper,robots in three typical high-speed railway station map environments are simulated to demonstrated that the algorithm can improve the path safety and convergence speed.(2)In the section of local path planning,aiming at the drawbacks of the classical Artificial Potential Field,such as the inability to reach the target points and the tendency to be caught in local minimum,the potential field function is modified and an escape strategy is proposed to solve the problems.Firstly,by changing the repulsive potential field function and the gravitational potential field function,the unreachable target problem and the gravitational deficiency problem are solved.Then different escape strategies are proposed to solve the problem of falling into local minimum and concave trap respectively.Finally,Python simulation proves the feasibility of the modified algorithm and escape strategy in different environments.(3)Aiming at the actual environment of high-speed railway terminals,this paper proposes a hybrid algorithm combining the modified global and local path planning algorithms.Firstly,Gazebo,the 3D physical simulation platform provided by ROS,is used to build the environment map,and then Rviz,a 3D visualization tool,is used to observe the sensing information and the situation of path planning obtained by the inspection robot.Finally,the constructed mobile robot model was simulated to test the hybrid algorithm in the simulation environment.The experimental findings suggest that the hybrid algorithm can make the inspection robot reach the target location safely and the algorithm is of high efficiency in both static and dynamic uncertain surroundings,indicating that the hybrid algorithm is feasible in the actual environment.