- University of Washington
- Seattle, Washington
- mohakbhardwaj.github.io
Highlights
- Pro
Stars
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.
Repo for paper DATT: Deep Adaptive Trajectory Tracking for Quadrotor Drones
High-performance C++ multibody dynamics/physics library for simulating articulated biomechanical and mechanical systems like vehicles, robots, and the human skeleton.
A GPU accelerated library for computing rigid body dynamics with analytical gradients
Stochastic Tensor Optimization for Robot Motion - A GPU Robot Motion Toolkit
An offline deep reinforcement learning library
Multi-Joint dynamics with Contact. A general purpose physics simulator.
📺 Discover the latest machine learning / AI courses on YouTube.
Deep Reinforcement Learning for Robotic Grasping from Octrees
RL starter files in order to immediately train, visualize and evaluate an agent without writing any line of code
Simple and easily configurable grid world environments for reinforcement learning
PyTorch implementation of soft actor critic
PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
A toolkit for reproducible reinforcement learning research.
A repository of various URDFs and assets needed for robot manipulation
Trajectory optimization algorithms for robotic control.
Reinforcement learning algorithms for MuJoCo tasks
A general and flexible factor graph non-linear least square optimization framework
Datasets for testing graph collision checking algorithms
Bunch of utility scripts to process videos / timelapse images I take with an action cam.


