NVIDIA-Jetson / redtail

https://github.com/NVIDIA-Jetson/redtail

Perception and AI components for autonomous mobile robotics.

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.
https://github.com/NVIDIA-Jetson/redtail/wiki
协助无人机穿越林地的软件 - NVIDIA Redtail 项目包括深度神经网络、计算机视觉和控制代码、硬件指令等，用户可借以打造一款能够自主导航通过森间小径或城市道路等挑战性环境的无人机或地面车辆。
NVIDIA 自主研发的导航开源项目 Redtail，探索通过深度学习技术实现无人机自主寻找路径的解决方案。无论是人迹罕至的森林深处，还是工业无人区，该技术都能够帮助无人机在具有挑战性的环境中自主导航，这将在救援、工业探伤等领域得到应用。

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.
[Toward Low-Flying Autonomous MAV Trail Navigation using Deep Neural Networks for Environmental Awareness]

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.
https://github.com/NVIDIA-Jetson/redtail/tree/master/models/pretrained
https://github.com/NVIDIA-Jetson/redtail/wiki/Models

The project also contains Stereo DNN models and runtime which allow to estimate depth from stereo camera on NVIDIA platforms.
https://github.com/NVIDIA-Jetson/redtail/tree/master/stereoDNN

CVPR 2018: we will present our work at CVPR 2018 conference as a part of Workshop on Autonomous Driving. Feel free to stop by and chat.
http://cvpr2018.thecvf.com/
http://www.wad.ai/index.html

References and Demos

NVIDIA-Jetson/redtail:
https://github.com/NVIDIA-Jetson/redtail/wiki

Toward Low-Flying Autonomous MAV Trail Navigation using Deep Neural Networks for Environmental Awareness
NVIDIA-Jetson/redtail/models/pretrained/:
https://github.com/NVIDIA-Jetson/redtail/tree/master/models/pretrained

NVIDIA-Jetson/redtail:
https://github.com/NVIDIA-Jetson/redtail/wiki/Models

NVIDIA-Jetson/redtail/stereoDNN/:
https://github.com/NVIDIA-Jetson/redtail/tree/master/stereoDNN

Stereo DNN, CVPR18 paper, Stereo DNN video demo
On the Importance of Stereo for Accurate Depth Estimation: An Efficient Semi-Supervised Deep Neural Network Approach
https://www.youtube.com/watch?v=0FPQdVOYoAU&feature=youtu.be

TrailNet Forest Drone Navigation, IROS17 paper, TrailNet DNN video demo
[Toward Low-Flying Autonomous MAV Trail Navigation using Deep Neural Networks for Environmental Awareness]
https://www.youtube.com/watch?v=H7Ym3DMSGms&feature=youtu.be

GTC 2017 talk: slides, video
http://on-demand.gputechconf.com/gtc/2017/presentation/s7172-nikolai-smolyanskiy-autonomous-drone-navigation-with-deep-learning.pdf
http://on-demand.gputechconf.com/gtc/2017/video/s7172-smolyanskiy-autonomous-drone-navigation-with-deep-learning%20(1).PNG.mp4

Demo video showing 250m autonomous flight with TrailNet DNN flying the drone
https://www.youtube.com/watch?v=H7Ym3DMSGms&feature=youtu.be

Demo video showing our 1 kilometer autonomous drone flight with TrailNet DNN
https://www.youtube.com/watch?v=USYlt9t0lZY&feature=youtu.be

Demo video showing TrailNet DNN driving a robotic rover around the office
https://www.youtube.com/watch?v=lOmT4yWcJrM&feature=youtu.be

Demo video showing TrailNet generalization to ground vehicles and other environments
https://www.youtube.com/watch?v=ZKF5N8xUxfw&feature=youtu.be

Wordbook

autonomous [ɔː’tɒnəməs]：adj. 自治的，自主的，自发的
robotic [ro’bɑtɪk]：adj. 机器人的，像机器人的，自动的 n. 机器人学
drone [drəʊn]：n. 雄蜂，嗡嗡的声音，懒惰者 n. 无人机（非正式） vi. 嗡嗡作声，混日子 vt. 低沉地说
artifact ['ɑ:təˌfækt]：n. 人工制品，手工艺品
forest trail：林荫小径，林间小径
sidewalk ['saɪdwɔːk]：n. 人行道