Optimization Of Positioning And Path Planning Algorithm For Indoor Mobile Robot

With the development of artificial technology,computer science,sensor technology,and electronic information engineering technology,intelligent robot technology has also advanced greatly and begin to enter people's daily life.This project designed a set of indoor mobile robot research platform IIMR-I,and focused on the optimization and improvement of positioning and path planning algorithms.The research content of this paper mainly includes the following aspects.Firstly,based on the application environment and functional requirements of the robot,we selected the appropriate robot hardware equipment,and designed the indoor mobile platform IIMR-I using Robot Operating System.It's application scenarios are mainly indoor,office,exhibition hall and other indoor places.The robot is modular in design and can divided into two layers:the embedded bottom layer and PC layer.The embedded bottom layer includes a base drive system,a base control system,and a sensor system;The PC layer is responsible for calculating robot algorithm,transferring communication,realizing simultaneous localization and mapping,path planning,and self-positioning in navigation process based on ROS,etc.Then,we optimized the AMCL algorithm,and proposed using ORB algorithm to match the key points detected from static global map and real-time local map to generate sampling particles and improved the global positioning ability of AMCL.Our simulation experiments showed that the optimized AMCL algorithm could insert sampled particles in the correct pose and realized global positioning of the robot as the particle is updated.Finally,we optimized the basic RRT path planning algorithm on the IIMR-I experimental platform.The target point is preferentially selected as the new extended child node,and the last extended parent node is used as the current extended parent node.Only when the path is blocked by the obstacle,the node is randomly selected as the extended direction and the extended child node,thereby the extended nodes of the RRT algorithm have directionality and improves the path search efficiency.We tested the improved RRT path planning algorithm in the real map environment,and verified the reliability of the algorithm.