Deep reinforcement learning for simultaneous robotic manipulation and locomotion
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Updated
Jul 18, 2020 - Python
Deep reinforcement learning for simultaneous robotic manipulation and locomotion
This repository is includes the code used in the paper: TraMiner: Vision-based Analysis of Locomotion Traces for Cognitive Assessment in Smart-homes
Automatic muscle tendon junction tracking using deep learning 🦵🏼
Repository for Final Design, "Motion Control Method for Small Quadruped Robots Based on Trajectory Modulation and Reinforcement Learning" (基于轨迹调制和强化学习的小型四足机器人运动控制方法)
Newtonian mechanics model for C. elegans locomotion
Simulations for snake kinematics with anisotropic friction.
Model predictive control to balance Upkie wheeled bipeds
Genetic Programming was used to build nonlinear models of data gathered from a smartwatch. Results were actually amazing and will be published.
This package computes the Improved Feasible Region. This is an intersection between the Feasible Region (Orsolino, 2020) and the Reachable Region (a 2D level area representing the CoM reachable workspace). The details are explained in this preprint:
Python algorithm to assess muscle activation patterns during cyclical movements
Upkie agent that can balance and crouch
[ICML 2023 Oral] Official environments and implementations for "Subequivariant Graph Reinforcement Learning in 3D Environments"
Train a balancing policy for Upkie by reinforcement learning
A neuromechanical model of adult Drosophila melanogaster.
Universal locomotion control package for holonomic rovers for ROS framework
Train the motion to make your robot move as expected
Unsupervised Cross-subject Adaptation for Predicting Human Locomotion Intent
Agile Quadruped Locomotion RL based on bullet
A model predictive controller for quadruped robots based on the single rigid body model and written in python. Gradient-based (acados) or Sampling-based (jax).
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