Robotics & Machine Learning Daily News2024,Issue(Feb.2) :58-58.DOI:10.1109/JSEN.2023.3317286

Data from Northwestern Polytechnic University Advance Knowledge in Robotics (Center of Mass Dynamics and Contact-aided Invariant Filtering for Biped Robot State Estimation)

Robotics & Machine Learning Daily News2024,Issue(Feb.2) :58-58.DOI:10.1109/JSEN.2023.3317286

Data from Northwestern Polytechnic University Advance Knowledge in Robotics (Center of Mass Dynamics and Contact-aided Invariant Filtering for Biped Robot State Estimation)

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Abstract

2024 FEB 02 (NewsRx) – By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Robotics is the subject of a report. According to news reporting out of Xi’an, People’s Republic of China, by NewsRx editors, research stated, “Due to the complexity and uncertainty of the actual working environments, relying solely on proprioceptive sensors to obtain accurate floating base and center of mass (CoM) estimates is of great significance for biped robots. In this article, a biped locomotion state estimator aided by both CoM dynamics and leg forward kinematics is proposed.” Our news journalists obtained a quote from the research from Northwestern Polytechnic University, “The main contribution of this estimator is the use of contact force measurements that are not considered in existing methods. Contact force measurements can be used to predict CoM motions and update the floating base estimates with CoM forward kinematics. Compared with the leg forward kinematics, the CoM dynamics prediction and the CoM forward kinematics update are more robust to contact slippage and highly dynamic motions. The simulation results show that the estimator proposed in this article improves the estimation accuracy of the floating base in the slippage direction under various reference speeds.”

Key words

Xi’an/People’s Republic of China/Asia/Emerging Technologies/Machine Learning/Robot/Robotics/Northwestern Polytechnic University

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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