Sim-to-real RL training and deployment tools for the Unitree Go1 robot.

[NeurIPS 2022] 🛒WebShop: Towards Scalable Real-World Web Interaction with Grounded Language Agents

A Gazebo simulator for the Franka Emika Panda robot with ROS interface, supporting sim-to-real code transfer (Python). Exposes customisable controllers and state feedback from robot in simulation.

[RSS 2024]: Expressive Whole-Body Control for Humanoid Robots

Suite of PyBullet reinforcement learning environments targeted towards using tactile data as the main form of observation.

[CVPR'22] CrossLoc localization: a cross-modal visual representation learning method for absolute localization

UR10 Reacher Reinforcement Learning Sim2Real Environment for Omniverse Isaac Gym/Sim

🗺🤖🚘🕹📡 An effective, easy-to-implement, and low-cost modular framework for completing complex navigation tasks.

reinforcement learning from randomized simulations

Dofbot Reacher Reinforcement Learning Sim2Real Environment for Omniverse Isaac Gym/Sim

Pytorch Implementation of SimGAN: Hybrid Simulator Identification for Domain Adaptation via Adversarial Reinforcement Learning, ICRA 2021

[ICRA 2024 Workshop] DriveEnv-NeRF: Exploration of A NeRF-Based Autonomous Driving Environment for Real-World Performance Validation

[CVPR'22] TOPO-DataGen: an open and scalable aerial synthetic data generation workflow

Simulation environments for the CrazyFlie quadrotor: Used for Reinforcement Learning and Sim-to-Real Transfer

DROPO: Sim-to-Real Transfer with Offline Domain Randomization

[CVPR'22] CrossLoc benchmark datasets setup and helper scripts.

The repository is intended as a support tool for the report of the project "Sim to Real transfer of Reinforcement Learning Policies in Robotics" and it contains examples of some well-known algorithms and methods in the fields of Reinforcement Learning and Sim-to-Real transfer. The implementation is not thought to be efficient, thus we suggest yo…

Sim-to-Real Domain Adaptation for Lane Detection and Classification in Autonomous Driving

Code for paper on ICRA 2022 workshop on Deformable Object Manipulation. In this work we learn keypoints from synthetic data for robotic cloth folding.

Enabling Faster Training of Robust Reinforcement Learning Policies for Soft Robots