There are 5 repositories under learning-from-demonstration topic.
🤖 The Full Process Python Package for Robot Learning from Demonstration and Robot Manipulation
Implementation of Inverse Reinforcement Learning (IRL) algorithms in Python/Tensorflow. Deep MaxEnt, MaxEnt, LPIRL
Implementation of Inverse Reinforcement Learning Algorithm on a toy car in a 2D world problem, (Apprenticeship Learning via Inverse Reinforcement Learning Abbeel & Ng, 2004)
Implementation of the paper "Overcoming Exploration in Reinforcement Learning with Demonstrations" Nair et al. over the HER baselines from OpenAI
Assetto Corsa OpenAI Gym Environment
"Good Robot! Now Watch This!": Repurposing Reinforcement Learning for Task-to-Task Transfer; and “Good Robot!”: Efficient Reinforcement Learning for Multi-Step Visual Tasks with Sim to Real Transfer
Integrating learning and task planning for robots with Keras, including simulation, real robot, and multiple dataset support.
A robot learning from demonstration framework that trains a recurrent neural network for autonomous task execution
Kernelized Movement Primitives (KMP)
[CVPR 2025] Tra-MoE: Learning Trajectory Prediction Model from Multiple Domains for Adaptive Policy Conditioning
Train a robot to see the environment and autonomously perform different tasks
Dynamic Motion Primitives
Code for the paper Continual Learning from Demonstration of Robotic Skills
An implementation of Deep Q-Learning from Demonstrations (DQfD) for playing Atari 2600 video games
[ICRA 2024] Learning from Human Guidance: Uncertainty-aware deep reinforcement learning for autonomous driving.
[ICLR 2022 Spotlight] Code for Reinforcement Learning with Sparse Rewards using Guidance from Offline Demonstration
REvolveR: Continuous Evolutionary Models for Robot-to-robot Policy Transfer (ICML 2022 Long Oral)
Online Signal Temporal Logic (STL) Monte-Carlo Tree Search for Guided Imitation Learning
A framework and method to jointly learn a (neural) control objective function and a time-warping function only from sparse demonstrations or waypoints.
Inverse optimal control from incomplete trajectory observations, proposing the concept of the recovery matrix which provides further insights into objective learning process.
RAMPA: Robotic Augmented Reality for Machine Programming by Demonstration https://arxiv.org/abs/2410.13412
Implementation of the paper "Human-like Planning for Reaching in Cluttered Environments" (ICRA 2020)
Stable dynamical system (motion policy) learning using Euclideanizing flows
PyTorch code for TAPAS-GMM.
[NeurIPS 2022] Code for Enhanced Meta Reinforcement Learning using Demonstrations in Sparse Reward Environments
Learning second order dynamical system
ABC-DS: obstacle Avoidance with Barrier-Certified polynomial Dynamical Systems
[T-RO] Python implementation of PRobabilistically-Informed Motion Primitives (PRIMP)
Learning simple tasks with Kinova Gen3 robot
This repository contains the source code for our paper: "Feedback-efficient Active Preference Learning for Socially Aware Robot Navigation", accepted to IROS-2022. For more details, please refer to our project website at https://sites.google.com/view/san-fapl.
[T-RO] MATLAB implementation of PRobabilistically-Informed Motion Primitives (PRIMP), a learning-from-demonstration method on Lie group.
Code for the paper Exploring the Properties of Hypernetworks for Continual Learning in Robotics.
This repository hosts the physical robot code for ToolFlowNet. Published at CoRL '22.