[IEEE T-PAMI 2024] All you need for End-to-end Autonomous Driving

A comprehensive list of papers about Robot Manipulation, including papers, codes, and related websites.

A curated list of 3D Vision papers relating to Robotics domain in the era of large models i.e. LLMs/VLMs, inspired by awesome-computer-vision, including papers, codes, and related websites

[CVPR 2024 Highlight] GenAD: Generalized Predictive Model for Autonomous Driving

YLearn, a pun of "learn why", is a python package for causal inference

AlpaGym is a reinforcement-learning framework for end-to-end autonomous-driving policies.

[ICLR 2023] Pytorch implementation of PPGeo, a fully self-supervised driving policy pre-training framework to learn from unlabeled driving videos.

[RSS 2024] Learning Manipulation by Predicting Interaction

[RSS 2026 Finalist] Ordered Action Tokenization

Policy learning via doubly robust empirical welfare maximization over trees

[ECCV 2022] Learning to Drive by Watching YouTube Videos: Action-Conditioned Contrastive Policy Pretraining

Stable dynamical system (motion policy) learning using Euclideanizing flows

PyTorch code for TAPAS-GMM.

Experiment code for "Koopman Constrained Policy Optimization: a Koopman operator theoretic method for differentiable optimal control in robotics" as presented at ICML 2023

Off-Policy Evaluation and Learning that is both Doubly Robust and Distributionally Robust.

[RA-L 2026] Factorized Diffusion Policy

Black-box, gradient-free optimization of car-racing policies.

This package supports global planning and meta-control for AI agents tackling complex, long-horizon tasks, reducing costly strategic mistakes and blind trial-and-error search.

The official repository for Net Actor-Critic

[ECAI-2025] SPOWL: A JAX-based Safe RL framework that adaptively combines planning and policy learning with dynamic safety thresholds.