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NVIDIA Redtail project

Autonomous visual navigation components for drones and ground vehicles using deep learning. Refer to wiki for more information on how to get started.

This project contains deep neural networks, computer vision and control code, hardware instructions and other artifacts that allow users to build a drone or a ground vehicle which can autonomously navigate through highly unstructured environments like forest trails, sidewalks, etc. Our TrailNet DNN for visual navigation is running on NVIDIA's Jetson embedded platform. Our arXiv paper describes TrailNet and other runtime modules in detail.

The project's deep neural networks (DNNs) can be trained from scratch using publicly available data. A few pre-trained DNNs are also available as a part of this project. In case you want to train TrailNet DNN from scratch, follow the steps on this page.

The project also contains Stereo DNN models and runtime which allow to estimate depth from stereo camera on NVIDIA platforms.

IROS 2018: we presented our work at IROS 2018 conference as a part of Vision-based Drones: What's Next? workshop.

CVPR 2018: we presented our work at CVPR 2018 conference as a part of Workshop on Autonomous Driving.

References and Demos

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