Autoware - the world's leading open-source software project for autonomous driving
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Updated
May 29, 2024 - Shell
Autoware - the world's leading open-source software project for autonomous driving
Toolbox for Map Conversion and Scenario Creation for Autonomous Vehicles.
CVPR 2023-2024 Papers: Dive into advanced research presented at the leading computer vision conference. Keep up to date with the latest developments in computer vision and deep learning. Code included. ⭐ support visual intelligence development!
An open autonomous driving platform
Open-source simulator for autonomous driving research.
This repository hosts the implementation of autonomous vehicle navigation using RL techniques, with a specific emphasis on Deep Q-Networks (DQN) and Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithms. We focus on training a TurtleBot3 robot to navigate autonomously through environments while intelligently avoiding moving obstacles.
RoboBEV: Towards Robust Bird's Eye View Perception under Common Corruption and Domain Shift
Autonomous driving episode generation for the Carla simulator in a gym environment. This framework makes it easy to create driving scenarios to train/test the agent.
Multi-task learning using message passing graph neural network for radar based perception functions
A curated list of world models for autonomous driving. Keep updated.
Convert Vegvesen NVDB road network to OpenDrive
Collect some World Models for Autonomous Driving papers.
Autonomous Driving W/ Deep Reinforcement Learning in 3D environment
This repository is a paper digest of recent advances in collaborative / cooperative / multi-agent perception for V2I / V2V / V2X autonomous driving scenario.
Python sample codes for robotics algorithms.
A collection of some awesome public object detection and recognition datasets.
📦 eCAL - enhanced Communication Abstraction Layer. A high performance publish-subscribe, client-server cross-plattform middleware.
Tactics2D: A Reinforcement Learning Environment Library with Generative Scenarios for Driving Decision-making
[Incl. GenAD, CVPR 2024 Highlight] Embracing Foundation Models into Autonomous Agent and System
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