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Learning to play table tennis from scratch using muscular robots
Dynamic tasks such as table tennis are relatively easy to learn for humans, but pose
significant challenges to robots. Such tasks require accurate control of fast movements and …
significant challenges to robots. Such tasks require accurate control of fast movements and …
Semi-parametric musculoskeletal model for reinforcement learning-based trajectory tracking
H Xu, J Fan, H Ma, Q Wang - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
This article aims to solve the trajectory tracking task of the pneumatic musculoskeletal robot
within a model-based reinforcement learning framework. Considering the limited sensors …
within a model-based reinforcement learning framework. Considering the limited sensors …
Machine learning for musculoskeletal modeling of upper extremity
We propose a novel machine learning (ML)-driven methodology to estimate biomechanical
variables of interest traditionally obtained from upper-extremity musculoskeletal (MSK) …
variables of interest traditionally obtained from upper-extremity musculoskeletal (MSK) …
Utilising redundancy in musculoskeletal systems for adaptive stiffness and muscle failure compensation: a model-free inverse statics approach
Vertebrates possess a biomechanical structure with redundant muscles, enabling
adaptability in uncertain and complex environments. Harnessing this inspiration …
adaptability in uncertain and complex environments. Harnessing this inspiration …
Robust continuous motion strategy against muscle rupture using online learning of redundant intersensory networks for musculoskeletal humanoids
Musculoskeletal humanoids have various biomimetic advantages, of which redundant
muscle arrangement is one of the most important features. This feature enables variable …
muscle arrangement is one of the most important features. This feature enables variable …
Learning to control highly accelerated ballistic movements on muscular robots
High-speed and high-acceleration movements are inherently hard to control. Applying
learning to the control of such motions on anthropomorphic robot arms can improve the …
learning to the control of such motions on anthropomorphic robot arms can improve the …
A learnable safety measure
Failures are challenging for learning to control physical systems since they risk damage,
time-consuming resets, and often provide little gradient information. Adding safety …
time-consuming resets, and often provide little gradient information. Adding safety …
Characterization of continuum robot arms under reinforcement learning and derived improvements
In robotics, soft continuum robot arms are a promising prospect owing to their redundancy
and passivity; however, no comprehensive study exists that examines their characteristics …
and passivity; however, no comprehensive study exists that examines their characteristics …
Model-based reinforcement learning for trajectory tracking of musculoskeletal robots
H Xu, J Fan, Q Wang - 2023 IEEE International Instrumentation …, 2023 - ieeexplore.ieee.org
This paper aims to solve the trajectory tracking task of the pneumatic musculoskeletal robot
within a model-based reinforcement learning framework. Considering the limited sensors …
within a model-based reinforcement learning framework. Considering the limited sensors …
Safe & Accurate at Speed with Tendons: A Robot Arm for Exploring Dynamic Motion
S Guist, J Schneider, H Ma, L Chen, V Berenz… - arxiv preprint arxiv …, 2023 - arxiv.org
Operating robots precisely and at high speeds has been a long-standing goal of robotics
research. Balancing these competing demands is key to enabling the seamless …
research. Balancing these competing demands is key to enabling the seamless …