Research On Self-Construction And Navigation Technology Of Coal Mine Rescue Robot

In recent years,with the development of science and technology,especially in the field of artificial intelligence,robotics and computers.The research and development of autonomous mobile robots has made great progress.Rescue robots for mobile robots to detect in the post-disaster scene have also begun to appear.The mobile robot replaces rescuers to perform tasks for detecting environmental information at the disaster site.The self-detected rescue robot is mainly inseparable from the environment and its own location awareness.These two technologies are collectively referred to as Simultaneous Location and Mapping(SLAM).SLAM technology is a research hotspot and key technology in the field of mobile robots.This topic takes the coal mine rescue robot as the application background,and studies the methods of robot technology in positioning and map construction,navigation and path planning.At the same time,a prototype of coal mine rescue robot integrating embedded,software application,map construction and path planning is constructed.(1)The application of SLAM technology in mobile robots is introduced.It also briefly summarizes its research background,significance and research status at home and abroad.The application scenarios and research directions of SLAM technology are introduced,and the research direction of the subject is determined.(2)The mobile robot motion model and observation model of the experimental platform are studied and modeled,and the system construction of robot operating system(ROS)and lidar is studied.The basic working principle of laser radar scanning unknown environment and the establishment of laser radar-based observation model are introduced in detail.The basic framework and advantages of ROS system are also introduced.(3)Research on the laser radar-based SLAM algorithm for the composition of robots.Directly discarding low-weight particles during resampling for the RBPF-SLAM algorithm can easily lead to problems such as particle depletion and particle diversity reduction.The quantum particle swarm optimization algorithm is introduced into RBPF-SLAM,and the particle set is adjusted to solve the phenomenon of particle depletion in resampling.Finally,the simulation experiment is carried out.The experimental results verify the feasibility of the RBPF-SLAM algorithm based on quantum particle swarm optimization and alleviate the problem of particle depletion.(4)Next,research is conducted on robot navigation based on SLAM providing an environmental map.The navigation algorithm is studied in both directions of global and local path planning.In view of these two directions,this paper proposes two algorithms,and verifies the effectiveness of the algorithm in ROS.Finally,the control of the experimental platform is realized in ROS.(5)Based on ROS platform,a comprehensive system framework of mobile robot experimental platform was designed and built.SLAM,path planning,underlying control,coordinate transformation and remote control modules were built.Real-time map construction and positioning of mobile robots based on real environment,local navigation and obstacle avoidance verification.The experiment proves the feasibility of SLAM system and mobile robot system based on ROS design.Figure [62] table [4] reference [56].