dtbinh Goto Github PK

rl-book

rl-book-overleaf

rl-collision-avoidance

Implementation of the paper "Towards Optimally Decentralized Multi-Robot Collision Avoidance via Deep Reinforcement Learning"

rl-delay

Reinforcement learning in real-time control system with delay

rl-dwa

Using stable-baselines3 'PPO' reinforcement learning algorithm to train dynamic window approach

rl-indirect-imitation

Pytorch code for "State-only Imitation with Transition Dynamics Mismatch" (ICLR 2020)

rl-itg

Learning-based Initialization of Trajectory Optimization for Path-following Problems of Redundant Manipulators (ICRA23)

rl-on-vrep

A testbed for RL research using V-REP

rl-robot

Reinforcement Learning framework for Robotics

rl-tutorial-jnrr19

Stable-Baselines tutorial for Journées Nationales de la Recherche en Robotique 2019

rl4mapf

Reinforcement Learning for Multi-Agent Path Finding

rl4vlm

Official Repo for Fine-Tuning Large Vision-Language Models as Decision-Making Agents via Reinforcement Learning

rlca_trainning

rlhf-ppo

Notes and commented code for RLHF (PPO)

rlkit

Collection of reinforcement learning algorithms

rllib

C++ Template Library to Predict, Control, Learn Behaviors, and Represent Learnable Knowledge using On/Off Policy Reinforcement Learning

rlpyt

Reinforcement Learning in PyTorch

rlrobot

Reinforcement learning framework for robotics

rltool

Tools for reinforcement learning

rlts

rl_avoidance_gazebo

rl_collision_avoidance test in gazebo simulator

rl_exploration_for_uavs

Reinforcement Learning-based exploration algorithm to drive a fleet of UAVs in an unknown environment.

rl_local_planner

rl_matlab

rl_navigation

deep reinforcement learning for autonomous navigation

rl_rvo_nav

The source code of the [RA-L] paper "Reinforcement Learned Distributed Multi-Robot Navigation with Reciprocal Velocity Obstacle Shaped Rewards"

rmai2020-planning

rmbench-2022

In this work, we present RMBench, the first benchmark for robotic manipulations, which have high-dimensional continuous action and state spaces. We implement and evaluate reinforcement learning algorithms that directly use observed pixels as inputs.

rmf_demos

Demonstrations of the OpenRMF software

rmpc

introducing Robust Model Predictive Control code