- University of Washington
- Seattle, Washington
- mohakbhardwaj.github.io
Highlights
- Pro
Stars
PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
Simple and easily configurable grid world environments for reinforcement learning
A toolkit for reproducible reinforcement learning research.
An offline deep reinforcement learning library
PyTorch implementation of soft actor critic
RL starter files in order to immediately train, visualize and evaluate an agent without writing any line of code
Deep Reinforcement Learning for Robotic Grasping from Octrees
Reinforcement learning algorithms for MuJoCo tasks
Stochastic Tensor Optimization for Robot Motion - A GPU Robot Motion Toolkit
A GPU accelerated library for computing rigid body dynamics with analytical gradients
Trajectory optimization algorithms for robotic control.
Repo for paper DATT: Deep Adaptive Trajectory Tracking for Quadrotor Drones
A repository of various URDFs and assets needed for robot manipulation
A general model-free off-policy actor-critic implementation. Continuous and Discrete Soft Actor-Critic with multimodal observations, data augmentation, offline learning and behavioral cloning.
Bunch of utility scripts to process videos / timelapse images I take with an action cam.


