Reinforcement learning environments with musculoskeletal models
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Updated
Jan 24, 2022 - Python
Reinforcement learning environments with musculoskeletal models
Markerless kinematics with any cameras — From 2D Pose estimation to 3D OpenSim motion
Toolbox for using multiple cameras from intrinsic calculations to reconstructing kinematics
An OpenAI-Gym Package for Training and Testing Reinforcement Learning algorithms with OpenSim Models
Pose2Sim visualizer tool — Import cameras and OpenSim data in Blender
Example for using OpenSim with the QTM Project Automation Framework
A set of tools for linux for OpenSimulator management
This project sets up a simulation environment for forward walking dynamics using OpenSim in Google Colab. It involves installing necessary dependencies, handling datasets, and performing forward dynamics and inverse kinematics using pre-built models to simulate human gait analysis. Used Python libraries like Pandas, Plotly, and OpenSIm and
Scripts to produce ARFF files (Weka) from Opensim's database and logs
Design and optimization of printed AFO using musculoskeletal simulation.
This is my RL-DDPG implementation of osim-rl L2M2019 Environment (Work Still Under progress)
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