Výsledky vyhledávání - "Machine Learning for Robot Control"

Data-driven predictive control of nonholonomic robots based on a bilinear Koopman realization: Data does not replace geometry Autor Rosenfelder, Mario, Bold, Lea, Eschmann, Hannes, Eberhard, Peter, Worthmann, Karl, Ebel, Henrik

“…Advances in machine learning and the growing trend towards effortless data generation in real-world systems have led to an increasing interest for…”
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Linear Policies are Sufficient to Realize Robust Bipedal Walking on Challenging Terrains Autor Krishna, Lokesh, Castillo, Guillermo A., Mishra, Utkarsh A., Hereid, Ayonga, Kolathaya, Shishir

“…In this work, we demonstrate robust walking in the bipedal robot Digit on uneven terrains by just learning a single linear policy. In particular, we propose a…”
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Fast Payload Calibration for Sensorless Contact Estimation Using Model Pre-Training Autor Shan, Shilin, Pham, Quang-Cuong

“… However, these approaches show limitations in scenarios where robot dynamics, particularly the end-effector payload, are subject to changes…”
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Real-Time Constrained Tracking Control of Redundant Manipulators Using a Koopman-Zeroing Neural Network Framework Autor Sah, Chandan Kumar, Singh, Rajpal, Keshavan, Jishnu

“…This study proposes a combined Koopman-ZNN (Zeroing Neural Network) architecture for real-time control of redundant manipulators subject to input constraints…”
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Learning Optimal Impedance Control During Complex 3D Arm Movements Autor Naceri, Abdeldjallil, Schumacher, Tobias, Li, Qiang, Calinon, Sylvain, Ritter, Helge

“… In order to model human's stiffness adaptive skill, we give human subjects the task to reach for a target by moving a handle assembled on the end-effector of a compliant robotic arm…”
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Bridging the Model-Reality Gap With Lipschitz Network Adaptation Autor Zhou, Siqi, Pereida, Karime, Zhao, Wenda, Schoellig, Angela P.

“…As robots venture into the real world, they are subject to unmodeled dynamics and disturbances…”
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Learning Non-Parametric Models in Real Time via Online Generalized Product of Experts Autor Watson, Connor, Morimoto, Tania K.

“…In this work, we address the problem of online learning, where models must be continually updated from an incoming stream of data, while retaining past…”
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