Research On Autonomous Positioning Algorithm Of Indoor Service Robot

The increasing demand for service robot has led to the development of research on service robot technology,and indoor localization technology is one of the key technologies to ensure the normal operation of service robot,variable indoor environment and obstacle occlusion directly affect the indoor positioning accuracy of service robot.SLAM(simultaneous localization and mapping)algorithm allows for real-time estimation of the robot’s pose,however,traditional SLAM algorithms also have difficulty in performing high-precision localization due to their own defects or the influence of the surrounding environment.In this paper,the visual SLAM algorithm for indoor low light environment and the Fast SLAM algorithm based on particle filtering are studied and improved to improve the robot localization accuracy.The main research works are as follows:(1)Propose a visual SLAM optimization method in indoor low light environment.To address the problem of unclear image acquisition by vision SLAM in low light environment,which leads to the degradation of positioning accuracy,a vision SLAM front-end optimization method is proposed to enhance the graphics acquired by the service robot in low light indoor,improve the number of effective feature points and the matching accuracy between frames,and effectively improve the problem of inaccurate matching between front and back frames caused by the image quality.(2)Research on Fast SLAM algorithm based on improved particle filtering.To address the problem that the traditional particle filtering may have degraded weights and lost particle diversity,which leads to the degradation of prediction accuracy,a particle filtering based on the improved imperial butterfly algorithm is proposed,and then the improved particle filtering is applied to the Fast SLAM algorithm for robot localization simulation experiments.The experimental results show that the improved Fast SLAM algorithm can effectively improve the robot localization accuracy.(3)Perform the verification of service robot localization algorithm in indoor environment.The improved Fast SLAM algorithm and the classical Fast SLAM algorithm are compared and experimentally validated in robot simulation platform and real-world scenario.Build a robot indoor operation environment and establish a map,in the process of autonomous robot localization,the actual robot position values are extracted and compared with the estimated values of the algorithm,and the results prove that the algorithm in this paper has good localization effect when applied to actual robot localization.