gcastillom90

gcastillom90's Stars

• PWhiddy/PokemonRedExperiments

  Playing Pokemon Red with Reinforcement Learning

  Language:Jupyter Notebook7.1k73123650

• CarperAI/trlx

  A repo for distributed training of language models with Reinforcement Learning via Human Feedback (RLHF)

  Language:Python4.6k51292472

• pnnl/neuromancer

  Pytorch-based framework for solving parametric constrained optimization problems, physics-informed system identification, and parametric model predictive control.

  Language:Python9902871124

• PKU-Alignment/omnisafe

  JMLR: OmniSafe is an infrastructural framework for accelerating SafeRL research.

  Language:Python96640108132

• roboterax/humanoid-gym

  Humanoid-Gym: Reinforcement Learning for Humanoid Robot with Zero-Shot Sim2Real Transfer https://arxiv.org/abs/2404.05695

  Language:Python9451741151

• leggedrobotics/rsl_rl

  Fast and simple implementation of RL algorithms, designed to run fully on GPU.

  Language:Python8033329209

• curieuxjy/Awesome_Quadrupedal_Robots

  Awesome Quadrupedal Robots

  Language:Python61419269

• ydsf16/imu_gps_localization

  Using error-state Kalman filter to fuse the IMU and GPS data for localization.

  Language:C++609512173

• vikashplus/robohive

  A unified framework for robot learning

  Language:Python539114986

• silvery107/rl-mpc-locomotion

  Deep RL for MPC control of Quadruped Robot Locomotion

  Language:Python50552354

• abizovnuralem/go2_omniverse

  Unitree Go2, Unitree G1 support for Nvidia Isaac Lab (Isaac Gym / Isaac Sim)

  Language:Python467102741

• kevinzakka/mjctrl

  Minimal, clean, single-file implementations of common robotics controllers in MuJoCo.

  Language:Python2706918

• mit-biomimetics/fld

  Repository for our paper: FLD: Fourier Latent Dynamics for Structured Motion Representation and Learning, Proceedings of the 12th International Conference on Learning Representations (ICLR)

  Language:Python25641429

• miguelasd688/4-legged-robot-model

  Language:C++24929770

• fan-ziqi/robot_lab

  A generic robot RL library based on IsaacLab

  Language:Python2262821

• ZhengyiLuo/PULSE

  Official Implementation of the ICLR 2024 spotlight paper: Universal Humanoid Motion Representations for Physics-Based Control

  Language:Python1613179

• thomashirtz/notion-scholar

  Reference management solution using Python and Notion.

  Language:Python1585823

• isri-aist/BaselineWalkingController

  Humanoid walking controller with various baseline methods

  Language:C++134191621

• anindita127/IMoS

  "IMoS: Intent-Driven Fullbody Motion Synthesis for Human-Object Interaction". Proceeding of EUROGRAPHICS 2023.

  Language:Python855109

• zlr20/saferl_kit

  Language:Python67125

• lucidrains/anymal-belief-state-encoder-decoder-pytorch

  Implementation of the Belief State Encoder / Decoder in the new breakthrough robotics paper from ETH Zürich

  Language:Python65629

• rise-lab-skku/ICRA2023_Quadruped_Robot_Challenges

  Thie repository provides simulation map environment of ICRA2023 Quadruped Robot Challenges

  Language:CMake523211

• UT-Austin-RobIn/telemoma

  TeleMoMa: A Modular and Versatile Teleoperation System for Mobile Manipulation

  Language:Python49339

• zita-ch/terrain_benchmark

  terrain-robustness benchmark for legged locomotion

  Language:Jupyter Notebook43101

• martius-lab/cassi

  Repository for our paper: Versatile Skill Control via Self-supervised Adversarial Imitation of Unlabeled Mixed Motions. (ICRA 2023)

  Language:Python31002

• chaofiber/papers-robotics

  Notes of papers in robotics

  17200

• zaarAli/TB3-NED2-Robotics-project

  The project integrates ROS for precise robotic functioning, combining image acquisition, computer vision processing, and autonomous navigation with TurtleBot3.

  Language:Python16102

• pd-perry/RLIF

  Language:Python11121

• Digital-Humans-23/a2

  Language:C++41210

• UMich-BipedLab/Digit_Fall_Prediction_Dataset

  This dataset is comprised of simulation and hardware trajectories with various faults for the Digit robot during the task of standing. The simulation trajectories contain abrupt, incipient, and intermittent faults, while the hardware trajectories contain abrupt and incipient faults. A tutorial of the dataset can be found in the viz branch.

  Language:Jupyter Notebook3300