Indoor Quadruped Robot Navigation Algorithm Based on ORB-SLAM

Abstract

In recent years, the development of artificial intelligence, big data, and the Internet of Things technologies has revealed unprecedented potential and value in mobile robots across various sectors of automation and intelligence. Among these, quadruped robots have shown unique applications in the domain of indoor security and inspection, as they can navigate multi-storey buildings by ascending and descending stairs. To enhance the stability of visual navigation in indoor inspection environments for quadruped robots, this paper builds on the ORB-SLAM framework. It introduces the AGC algorithm to address the issue of reduced feature point extraction during night patrols, thereby increasing the number of feature points extracted. Additionally, to tackle the problem of high oscillation intensity during the movement of quadruped robots, the EKF algorithm has been incorporated for sensor fusion with IMU, enhancing the robustness of visual navigation. This has been validated through physical experiments.