From post

Bioinspired pneumatic muscle spring units mimicking the human motion apparatus: benefits for passive motion range and joint stiffness variation in antagonistic setups.

, , , , и . M2VIP, стр. 1-6. IEEE, (2018)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed.

 

Другие публикации лиц с тем же именем

Learning to Control Redundant Musculoskeletal Systems with Neural Networks and SQP: Exploiting Muscle Properties., , , , , , , и . ICRA, стр. 6461-6468. IEEE, (2018)Musculo-Skeletal Models as Tools to Quantify Embodiment., , и . ECAL, стр. 68. MIT Press, (2015)HOIMotion: Forecasting Human Motion During Human-Object Interactions Using Egocentric 3D Object Bounding Boxes., , , , и . CoRR, (2024)Morphological Computation Increases From Lower- to Higher-Level of Biological Motor Control Hierarchy., , , , и . Frontiers Robotics AI, (2020)GazeMotion: Gaze-guided Human Motion Forecasting., , , и . CoRR, (2024)Learning with Muscles: Benefits for Data-Efficiency and Robustness in Anthropomorphic Tasks., , , , , и . CoRL, том 205 из Proceedings of Machine Learning Research, стр. 1178-1188. PMLR, (2022)MyoChallenge 2022: Learning contact-rich manipulation using a musculoskeletal hand., , , , , , , , , и 19 other автор(ы). NeurIPS (Competition and Demos), том 220 из Proceedings of Machine Learning Research, стр. 233-250. PMLR, (2021)DEP-RL: Embodied Exploration for Reinforcement Learning in Overactuated and Musculoskeletal Systems., , , , и . ICLR, OpenReview.net, (2023)Simulating the response of a neuro-musculoskeletal model to assistive forces: implications for the design of wearables compensating for motor control deficits., , , и . BioRob, стр. 779-784. IEEE, (2020)Bioinspired pneumatic muscle spring units mimicking the human motion apparatus: benefits for passive motion range and joint stiffness variation in antagonistic setups., , , , и . M2VIP, стр. 1-6. IEEE, (2018)