demoa

A biophysics simulator for muscle-driven motion

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11 to 20 of 21 Results

allmin-3.0.tgz Jun 3, 2025 - allmin: A Reduced Human All-Body Model TAR Archive - 71.1 KB - MD5: 6e0d484243db14d4bed0db1b5fd93d21
LICENSE Jun 3, 2025 - allmin: A Reduced Human All-Body Model Plain Text - 1.5 KB - MD5: 1cd608add5724e6f8e1cc9bb99cee225
README.md Jun 3, 2025 - allmin: A Reduced Human All-Body Model Markdown Text - 1.9 KB - MD5: a28d7b07e57e74c877b5d53513a07a7d
MPC/OC Code for: Learning with Muscles: Benefits for Data-Efficiency and Robustness in Anthropomorphic Tasks Dec 16, 2022 Wochner, Isabell; Schmitt, Syn, 2022, "MPC/OC Code for: Learning with Muscles: Benefits for Data-Efficiency and Robustness in Anthropomorphic Tasks", https://doi.org/10.18419/DARUS-3268, DaRUS, V1 This code allows you reproduce the optimal control and model predictive control results of the paper: "Learning with Muscles: Benefits for Data-Efficiency and Robustness in Anthropomorphic Tasks" by Isabell Wochner, Pierre Schumacher, Georg Martius, Dieter Büchler, Syn Schmitt and Daniel F.B. Haeufle. Always cite the paper together with this datase...
mpc_oc_code_corl.tar.gz Dec 16, 2022 - MPC/OC Code for: Learning with Muscles: Benefits for Data-Efficiency and Robustness in Anthropomorphic Tasks Gzip Archive - 227.9 MB - MD5: 89792d633142a824f2a9e151d84d1594 Code for model predictive control (MPC) and optimal control (OC) to control musculoskeletal models in demoa. Please read ReadMe to find a description how to reproduce the numerical experiments of the paper.
README.md Dec 16, 2022 - MPC/OC Code for: Learning with Muscles: Benefits for Data-Efficiency and Robustness in Anthropomorphic Tasks Markdown Text - 4.7 KB - MD5: 5cbff34b49a706365c6874dc64fb1239 This file describes how to use and install the necessary code. Please read it to find out how to reproduce the experiments from the paper.
arm26: A Human Arm Model Oct 6, 2022 Wochner, Isabell; Schmitt, Syn, 2022, "arm26: A Human Arm Model", https://doi.org/10.18419/DARUS-2871, DaRUS, V2 An arm model parametrised using generic literature data for the geometry of the skeleton including attachment points for ligaments and muscles. This arm26 model consists of a musculoskeletal model of the arm with two degrees of freedom actuated by six muscles. The model is prepared to run muscle-driven simulation using a simple biological motor con...
arm26.tgz Oct 6, 2022 - arm26: A Human Arm Model Compressed Archive - 16.6 MB - MD5: fe30c7f2688fe1072cacef772ed7c760 Contains all files for the model, including the technical description and a readme file how to use/run the model.
README.md Oct 6, 2022 - arm26: A Human Arm Model Markdown Text - 6.0 KB - MD5: a61be801b2895d063bd1b27339baf96b This file describes how to install and use the model and how to run a first simple simulation.
Technical_Report_Allmin.pdf Jun 13, 2022 - allmin: A Reduced Human All-Body Model Adobe PDF - 1.4 MB - MD5: 51534f2243252e2f6177e836abb3c2f1 Supplementary material describing the allmin model.

allmin-3.0.tgz

Jun 3, 2025 - allmin: A Reduced Human All-Body Model

TAR Archive - 71.1 KB -

LICENSE

Jun 3, 2025 - allmin: A Reduced Human All-Body Model

Plain Text - 1.5 KB -

README.md

Jun 3, 2025 - allmin: A Reduced Human All-Body Model

Markdown Text - 1.9 KB -

MPC/OC Code for: Learning with Muscles: Benefits for Data-Efficiency and Robustness in Anthropomorphic Tasks

Dec 16, 2022

Wochner, Isabell; Schmitt, Syn, 2022, "MPC/OC Code for: Learning with Muscles: Benefits for Data-Efficiency and Robustness in Anthropomorphic Tasks", https://doi.org/10.18419/DARUS-3268, DaRUS, V1

This code allows you reproduce the optimal control and model predictive control results of the paper: "Learning with Muscles: Benefits for Data-Efficiency and Robustness in Anthropomorphic Tasks" by Isabell Wochner, Pierre Schumacher, Georg Martius, Dieter Büchler, Syn Schmitt and Daniel F.B. Haeufle. Always cite the paper together with this datase...

mpc_oc_code_corl.tar.gz

Dec 16, 2022 - MPC/OC Code for: Learning with Muscles: Benefits for Data-Efficiency and Robustness in Anthropomorphic Tasks

Gzip Archive - 227.9 MB -

Code for model predictive control (MPC) and optimal control (OC) to control musculoskeletal models in demoa. Please read ReadMe to find a description how to reproduce the numerical experiments of the paper.

README.md

Dec 16, 2022 - MPC/OC Code for: Learning with Muscles: Benefits for Data-Efficiency and Robustness in Anthropomorphic Tasks

Markdown Text - 4.7 KB -

This file describes how to use and install the necessary code. Please read it to find out how to reproduce the experiments from the paper.

arm26: A Human Arm Model

Oct 6, 2022

Wochner, Isabell; Schmitt, Syn, 2022, "arm26: A Human Arm Model", https://doi.org/10.18419/DARUS-2871, DaRUS, V2

An arm model parametrised using generic literature data for the geometry of the skeleton including attachment points for ligaments and muscles. This arm26 model consists of a musculoskeletal model of the arm with two degrees of freedom actuated by six muscles. The model is prepared to run muscle-driven simulation using a simple biological motor con...

arm26.tgz

Oct 6, 2022 - arm26: A Human Arm Model

Compressed Archive - 16.6 MB -

Contains all files for the model, including the technical description and a readme file how to use/run the model.

README.md

Oct 6, 2022 - arm26: A Human Arm Model

Markdown Text - 6.0 KB -

This file describes how to install and use the model and how to run a first simple simulation.

Technical_Report_Allmin.pdf

Jun 13, 2022 - allmin: A Reduced Human All-Body Model

Adobe PDF - 1.4 MB -

Supplementary material describing the allmin model.

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