vectrix
rex-gym
| vectrix | rex-gym | |
|---|---|---|
| 1 | 1 | |
| 6 | 957 | |
| - | - | |
| 10.0 | 0.0 | |
| over 1 year ago | about 1 year ago | |
| Python | Python | |
| MIT License | Apache License 2.0 |
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vectrix
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Suddenly can't connect to vector with SDK (no system changes I'm aware of)
So I've been using acidzebra's wonderful vectrix.py for a day or so, to keep vector active for my little one.
rex-gym
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By moving the battery pack forward, you can make the popular SpotMicro design balance much better. We had trouble getting it to do standing/walking because the center of mass was far to the back.
Our work was based on (SpotMicro)[https://github.com/michaelkubina/SpotMicroESP32] and (Rex Gym)[https://github.com/nicrusso7/rex-gym]. Our GitHub is (here)[https://github.com/LSaldyt/laser-dog]
What are some alternatives?
pycozmo - A pure-Python communication library, alternative SDK, and application for the Cozmo robot.
pybullet-gym - Open-source implementations of OpenAI Gym MuJoCo environments for use with the OpenAI Gym Reinforcement Learning Research Platform.
LOTP-RoboDog - This is my first quadruped robotic project which has still lots of things to do. I would like to share STL files, descriptions, components, instructions. But please be aware that this is just a test project which helps me to learn fundamentals of this science, and prepares myself for second prototype.
robot-gym - RL applied to robotics.
vector-python-sdk - Anki Vector Python SDK
drl_grasping - Deep Reinforcement Learning for Robotic Grasping from Octrees
PythonRobotics - Python sample codes for robotics algorithms.
PILCO - Bayesian Reinforcement Learning in Tensorflow
catgrasp - [ICRA 2022] CaTGrasp: Learning Category-Level Task-Relevant Grasping in Clutter from Simulation
stable-baselines3 - PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
gym-battleship - Battleship environment for reinforcement learning tasks
gretel-synthetics - Synthetic data generators for structured and unstructured text, featuring differentially private learning.