Vision-Assisted Localization and Terrain Reconstruction with Quadruped Robots

Legged robots, specifically quadruped robots, have good locomotion performance in complex and rugged terrain and are becoming widely used in field exploration and rescue missions. To achieve full autonomy in such scenarios, robots need not only accurate localization but also an accurate understanding of the surrounding terrain, which will be used for robots path planning and foothold planning. However, due to the kinetic characteristic and limitation of size, quadruped robots have the disadvantages of high-frequency jitter and limited field of sensors, which lead to some challenges in environmental perception. In this paper, we propose a vision-assisted rugged terrain environment reconstruction and localization method for quadruped robots. We use a depth camera to assist in the generation of high-precision localization and terrain reconstruction results, which can help achieve the autonomous mobility of quadruped robots in this environment. We test our method on a quadruped robot platform. Our experimental results show less error and lower drift in different stairs terrain types than the commonly used lidar-based localization method.