ROJul 6, 2020
Multi-Sensor State Estimation Fusion on Quadruped Robot Locomotion
arXiv:2007.02679v3
AI Analysis
This addresses the challenge of accurate localization and navigation for quadruped robots, which is incremental as it builds on existing sensor fusion methods.
The paper tackles the problem of state estimation for quadruped robot locomotion by fusing data from multiple sensors, including IMU, joint encoders, camera, and LIDAR, resulting in an effective algorithm.
In this paper, we present a effective state estimation algorithm that combined with various sensors information (Inertial measurement unit, joints encoder, camera and LIDAR)