Design Of P Ositioning And Navigation System For Inspection Robot Epidemic Prevention And Elimination

At the end of 2019,a sudden COVID-19 had a serious impact on our daily life.At the same time,we proposed the requirement of non-contact detection.In this paper,through the tracking of killing robot technology,aiming at the navigation system of epidemic prevention,killing and inspection robot,we mainly carry out three aspects:autonomous positioning and environmental composition analysis,path planning algorithm fusion and navigation system construction:(1)The error of SLAM problem of mobile robot is analyzed from the perspective of a posteriori probability.Through the research of SLAM algorithm based on Rao-Blackwelled particle filter,it is determined that the gmapping algorithm with improvement of the proposed distribution function and selective resampling strategy can effectively prevent particle regression and reduce particle diversity.(2)A-star algorithm and Time Elastic Band(TEB)algorithm to research the path planning and autonomous obstacle avoidance algorithm of inspection robot.The A-star algorithm can be used to obtain the global optimal path,and the TEB algorithm has good obstacle avoidance performance for dynamic obstacles.A hybrid path algorithm is proposed as a path planning strategy when the robot moves,which can accurately plan an effective path with strong foresight and optimal distance,so that the robot can move safely and smoothly to the target point.(3)Based on Ackermann robotics hardware platform with RPLIDAR and ROS software platform,the gmapping algorithm map construction experiment is carried out with the environment of different obstacle densities,and the obtained environment maps have clear outlines and obstacles,which verifies the accuracy and real-time of the algorithm.The robot path planning and obstacle avoidance experiments are conducted to verify that the hybrid path algorithm provides better path planning and dynamic obstacle avoidance capabilities.The analysis of the optimization strategy for autonomous charging of inspection robots based on the implementation of the navigation system is relevant to improve the efficiency of the robot.The simulation and experimental results show that the gmapping algorithm is used in both simulated and actual environments,and the optimal selection of its important parameters can improve the accuracy and real-time performance of the algorithm in constructing maps,and the use of hybrid path algorithm can realize path planning as well as dynamic obstacle avoidance.This paper effectively achieves the goal of accurate positioning navigation and hybrid dynamic path planning for epidemic prevention and disinfection inspection robots,and provides theoretical and technical support for realizing mobile service robots to complete epidemic prevention and disinfection inspection tasks quickly,accurately and safely.