pybullet
There are 198 repositories under pybullet topic.
bulletphysics/bullet3
Bullet Physics SDK: real-time collision detection and multi-physics simulation for VR, games, visual effects, robotics, machine learning etc.
DLR-RM/rl-baselines3-zoo
A training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.
utiasDSL/gym-pybullet-drones
PyBullet Gymnasium environments for single and multi-agent reinforcement learning of quadcopter control
araffin/rl-baselines-zoo
A collection of 100+ pre-trained RL agents using Stable Baselines, training and hyperparameter optimization included.
nicrusso7/rex-gym
OpenAI Gym environments for an open-source quadruped robot (SpotMicro)
benelot/pybullet-gym
Open-source implementations of OpenAI Gym MuJoCo environments for use with the OpenAI Gym Reinforcement Learning Research Platform.
OpenQuadruped/spot_mini_mini
Dynamics and Domain Randomized Gait Modulation with Bezier Curves for Sim-to-Real Legged Locomotion.
MushroomRL/mushroom-rl
Python library for Reinforcement Learning.
utiasDSL/safe-control-gym
PyBullet CartPole and Quadrotor environments—with CasADi symbolic a priori dynamics—for learning-based control and RL
araffin/robotics-rl-srl
S-RL Toolbox: Reinforcement Learning (RL) and State Representation Learning (SRL) for Robotics
google-research/ravens
Train robotic agents to learn pick and place with deep learning for vision-based manipulation in PyBullet. Transporter Nets, CoRL 2020.
RLE-Foundation/rllte
Long-Term Evolution Project of Reinforcement Learning
caelan/pybullet-planning
PyBullet Planning
caelan/pddlstream
PDDLStream: Integrating Symbolic Planners and Blackbox Samplers
RLE-Foundation/RLeXplore
RLeXplore provides stable baselines of exploration methods in reinforcement learning, such as intrinsic curiosity module (ICM), random network distillation (RND) and rewarding impact-driven exploration (RIDE).
Derek-TH-Wang/quadruped_ctrl
MIT mini cheetah quadruped robot simulated in pybullet environment using ros.
liruiw/GenSim
Generating Robotic Simulation Tasks via Large Language Models
BarisYazici/deep-rl-grasping
Train deep reinforcement learning model for robotics grasping. Choose from different perception layers raw Depth, RGBD and autoencoder. Test the learned models in different scenes and object datasets
AutonoBot-Lab/BestMan_Pybullet
Codebase for the BestMan Mobile Manipulator Platform
axelbr/racecar_gym
A gym environment for a miniature racecar using the pybullet physics engine.
ac-93/tactile_gym
Suite of PyBullet reinforcement learning environments targeted towards using tactile data as the main form of observation.
yijiangh/pybullet_planning
A suite of utility functions to facilitate robotic planning related research on the pybullet physics simulation engine.
mahyaret/kuka_rl
Reinforcement Learning Experiments using PyBullet
jjshoots/PyFlyt
UAV Flight Simulator for Reinforcement Learning Research
compas-dev/compas_fab
Robotic fabrication package for the COMPAS Framework.
nplan/gym-line-follower
Line follower robot simulator environment for Open AI Gym.
oscar-lima/pybullet_ros
A bridge between ROS and PyBullet
rainorangelemon/gnn-motion-planning
The official repo for NeurIPS 2021 paper 'Reducing Collision Checking for Sampling-Based Motion Planning Using Graph Neural Networks'
jimmyyhwu/spatial-intention-maps
Learning multi-agent robotic mobile manipulation with deep reinforcement learning
eleramp/pybullet-object-models
Collection of object models compatible with pybullet simulator https://github.com/bulletphysics/bullet3/tree/master/examples/pybullet
ChenEating716/pybullet-URDF-models
Collection of urdf models (including part of YCB dataset). Made for robot manipulation and grasping simulation, tested with PyBullet.
nikonikolov/rltf
Reinforcement Learning implementations and research prototyping in TensorFlow
mahyaret/gym-panda
An OpenAI Gym Env for Panda
caelan/SS-Replan
Online Replanning in Belief Space for Partially Observable Task and Motion Problems
SvenGronauer/Bullet-Safety-Gym
An open-source framework to benchmark and assess safety specifications of Reinforcement Learning problems.