Research On Indoor Mobile Robot Path Planning Based On ROS

Nowadays,since the subject of artificial intelligence and Science and technology has been developed rapidly,mobile robot technology has also been extensive used in industry,service industry,manufacturing and other fields accordingly.Among them,the path planning technology belongs to mobile robotics is one of the hot-spot topics in recent years,and it is also crucial to the realization of autonomous navigation of mobile robot.In the process of mobile path planning,according to the real-time nature of the assignment,it can be categorized into static global path planning and dynamic local path planning.This thesis addresses the shortcomings of the traditional known path planning algorithm and applies hybrid path planning algorithm to process the path planning task of the mobile robot.Also,in accordance with the A-star algorithm and the artificial potential field algorithm,and makes corresponding improvements to their problems respectively,this thesis proposes a hybrid path planning algorithm.The hybrid path planning algorithm is able to secure the optimal path while being able to dynamically dodge obstacles,improving the planning effectiveness of the algorithm.The principal tasks of this thesis are as shown below:1)Aiming at the problems of too many redundant points and path unsmoothness in A-star algorithm,firstly,the heuristic function of A-star algorithm is optimized,and secondly,redundant nodes are deleted by using node deletion strategy,finally,the tangent point method of angle bisector is proposed to smooth the path.The experimental results show that the improved A-star algorithm reduces the number of nodes by 60.47% in 15 * 15 raster map.2)By modifying the parameters of the repulsion field,the relative position term is inserted into the repulsion field function,which ensures the repulsion force of the mobile robot decreases continuously as it approaches the target point;In order to make sure the mobile robot can avoid obstacles on a real-time,the dynamic potential field is built,and a relative velocity term is incorporated into the gravitational and repulsive field functions,making the artificial potential field algorithm have the ability to deal with dynamic obstacles.The experimental results demonstrate that the modified artificial potential field algorithm can enhance the running time by13.92% and reduce the path length by 4%.3)Because the single algorithm is unable to fulfill the required criteria of the path planning task in the actual complicated in-door environment,the hybrid path algorithm is proposed.Firstly,the modified A-star algorithm is applied for carrying out the global path planning,and its core nodes are preserved,secondly,the core nodes are taken as the sub-target nodes in turn,finally,the optimized artificial potential field algorithm is invoked for its autonomous obstacle avoidance processing to guarantee the mobile robot is able to reach the target speedily and securely,and the efficacy of the hybrid algorithm is experimentally validated by the MATLAB simulation platform.4)For the purpose of verifying the feasibility of the algorithm,a Hands-Free robot platform was established and simulation experiments are conducted for different environments.The final experimental findings reveal that the mobile robot is capable of effectively avoiding dynamic obstacles while maintaining the optimal path.