Multi-Sensor State Estimation Fusion on Quadruped Robot Locomotion
Chen Yao, Zhenzhong Jia
TL;DR
This paper introduces a multi-sensor fusion algorithm for quadruped robot locomotion, integrating data from IMUs, encoders, cameras, and LIDAR to improve state estimation accuracy.
Contribution
It proposes a novel multi-sensor fusion approach specifically designed for quadruped robots, enhancing robustness and precision in state estimation.
Findings
Improved localization accuracy over single-sensor methods
Enhanced robustness in challenging environments
Effective integration of diverse sensor data
Abstract
In this paper, we present a effective state estimation algorithm that combined with various sensors information (Inertial measurement unit, joints encoder, camera and LIDAR)
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Taxonomy
TopicsRobotic Locomotion and Control · Robotics and Sensor-Based Localization · Robotics and Automated Systems