Real-time pose estimation of a dynamic quadruped in GPS-denied environments for 24-hour operation

Author:

Ma Jeremy1,Bajracharya Max12,Susca Sara1,Matthies Larry1,Malchano Matt3

Affiliation:

1. Jet Propulsion Laboratory, California Institute of Technology, USA

2. Currently with Google, Mountain View, USA

3. Boston Dynamics, Waltham, USA

Abstract

We present a real-time system that enables a highly capable dynamic quadruped robot to maintain an accurate six-degree-of-freedom pose estimate (within a 1.0% error of distance traveled) over long distances traversed through complex, dynamic outdoor terrain, during day and night, in the presence of camera occlusion and saturation, and occasional large external disturbances, such as slips or falls. The system fuses a stereo-camera sensor, inertial measurement unit, leg odometry, and optional intermittent GPS position updates with an extended Kalman filter to ensure robust, low-latency performance. To maintain a six-degree-of-freedom local positioning accuracy alongside the global positioning knowledge, two reference frames are used; a local reference frame and a global reference frame, with the former benefiting obstacle detection and mapping and the latter for operator-specified and autonomous way-point following. Extensive experimental results obtained from multiple field tests are presented to illustrate the performance and robustness of the system over hours of continuous runs and hundreds of kilometers of distance traveled in a wide variety of terrains and conditions.

Publisher

SAGE Publications

Subject

Applied Mathematics,Artificial Intelligence,Electrical and Electronic Engineering,Mechanical Engineering,Modelling and Simulation,Software

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3. Invariant Smoother for Legged Robot State Estimation With Dynamic Contact Event Information;IEEE Transactions on Robotics;2024

4. Locomotion Stability Control of Quadruped Robot Using the Combination of Ankle, Hip, and Step Strategies and Fuzzy Logic Controller;2023 3rd International Conference on Robotics, Automation and Artificial Intelligence (RAAI);2023-12-14

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