Computational reproductions of external force field adaption without assuming desired trajectories

DOI10.1016/J.NEUNET.2021.01.030zbMath1526.92003OpenAlexW3129738363MaRDI QIDQ6078727

Haruka Shimizu, Toshihiro Kawase, Yasuharu Koike, Nicolas Schweighofer, Natsue Yoshimura, Hiroyuki Kambara, Atsushi Takagi

Publication date: 28 September 2023

Published in: Neural Networks (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.neunet.2021.01.030

zbMATH Keywords

reinforcement learningmotor learningreaching movementforce-field adaptation

Mathematics Subject Classification ID

Neural networks for/in biological studies, artificial life and related topics (92B20) Biomechanics (92C10) Computational methods for problems pertaining to biology (92-08)

Cites Work

• A hierarchical neural-network model for control and learning of voluntary movement
• The control of hand equilibrium trajectories in multi-joint arm movements
• Estimation of dynamic joint torques and trajectory formation from surface electromyography signals using a neural network model
• Forward models for physiological motor control
• Dynamical Movement Primitives: Learning Attractor Models for Motor Behaviors

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