Research On Key Technologies Of Autonomous Navigation Of Service Robot

In recent years,due to factors such as the epidemic and the aging of the population,people's demand for non-face-to-face services has increased significantly,and service robots have become a focus of attention.The autonomous navigation ability of a service robot is a key factor affecting whether it can successfully complete the task.The localization technology is an indispensable part of the key technology of autonomous navigation of service robots.In order to improve the localization accuracy of the service robot when it moves according to the predetermined trajectory in the indoor environment,this paper takes the service robot with a three-wheeled omnidirectional mobile chassis as the research object to study the localization method of the service robot and other related issues.The main work of this paper is as follows:(1)Establish the localization system model of the service robot.The definition of the coordinate system and the transformation relationship between the coordinate systems of the service robot is given,and the kinematics model of the service robot is established.The kinematic modeling of the dead reckoning model and the lidar model of the odometer is carried out,and the errors of the two sensors are analyzed respectively.Through the analysis and introduction of the service robot environment map,combined with the characteristics of the service robot's working environment,the grid map is selected as the environment map studied in this paper.(2)Research on the localization method of the service robot.Aiming at the problems of low localization accuracy and poor stability of a single sensor when a service robot performs trajectory tracking and localization,a combined filtering trajectory tracking and localization method based on multi-sensor information fusion is proposed.Firstly,for the problem of noise in odometer data,Kalman filter is used to preprocess the odometer data.Then the multi-sensor information fusion algorithm is used to fuse the preprocessed odometer data and lidar data to improve the localization accuracy of service robot trajectory tracking.(3)Carry out simulation experiments and real-scene experimental verification.The simulation software is used to simulate the data preprocessing of the odometer to verify the effect of the data preprocessing.The proposed combined filtering trajectory tracking and localization method based on multi-sensor information fusion is simulated to verify the feasibility of the localization method.The experimental verification is carried out using the intelligent service robot experimental platform in an indoor environment.In summary,this paper conducts a preliminary study on the localization problem of service robots.The experimental results show that this method overcomes the defect of low localization accuracy of a single sensor,and to a certain extent improves the localization accuracy of the service robot when tracking the trajectory in the indoor environment.