The Study Of The Robot Indoor Based On Laser Vision

Currently,the robot industry is developing rapidly.A variety of robots and related technologies have emerged.Indoor robots are more common among them.The indoor mobile technology that guides its indoor walking requires various algorithms to coordinate with each other.These algorithms include positioning algorithms,scene analysis algorithms,real-time map building algorithms and so on.In addition,indoor robot mobile technology is often intertwined with technologies such as image processing and electronic communication.Its comprehensiveness is very complicated,which has become a hot research topic.This paper first summarizes and summarizes the domestic and international research status related to indoor robot walking technology.Then,according to the more complex characteristics of the laboratory environment,the demand analysis is carried out,the indoor robot scheme and the overall framework are designed,and the robot control scheme and system are selected.In the end,we applied the Lidar sensor and adopted SLAM plus simple navigation to realize the autonomous walking and mapping in the room.In addition,this paper also builds a mobile robot hardware platform,and performs various processing correction experiments on mobile robots,which improves the accuracy of map construction and paves the way for the subsequent of the experiments.Aiming at the topic of mobile robot indoor walking scheme,this paper builds a simulated mobile robot platform,analyzes the mobile robot indoor walking scheme,and improves the mobile robot walking scheme based on the actual needs based on the built platform framework.At the same time,the different framework algorithms in the platform are simulated and constructed,and then the algorithm is improved and debugged.The final algorithm has a significant improvement over the pre-improvement algorithm.Aiming at the poor mapping effect of robots and the large error of robot mapping in dynamic environment,the robot map processing algorithm is continuously debugged and improved,and the better map processing scheme is determined.Finally,the experiment verifies the effectiveness of the algorithm.