https://github.com/georgeerol/deeplearningdronesimulator

This project is about training a deep neural network to identify and track a target in simulation so-called “follow me”. Applications like this are key to many fields of robotics and the very same techniques you apply here can be extended to scenarios like advanced cruise control in autonomous vehicles or human-robot collaboration in industry.
https://github.com/georgeerol/deeplearningdronesimulator

deep-learning deep-neural-networks robotics segmentation simulation tensorflow

Last synced: about 2 months ago
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This project is about training a deep neural network to identify and track a target in simulation so-called “follow me”. Applications like this are key to many fields of robotics and the very same techniques you apply here can be extended to scenarios like advanced cruise control in autonomous vehicles or human-robot collaboration in industry.

• Host: GitHub
• URL: https://github.com/georgeerol/deeplearningdronesimulator
• Owner: georgeerol
• Created: 2017-11-11T00:30:03.000Z (about 7 years ago)
• Default Branch: master
• Last Pushed: 2018-04-12T15:58:10.000Z (over 6 years ago)
• Last Synced: 2023-10-20T19:58:46.492Z (about 1 year ago)
• Topics: deep-learning, deep-neural-networks, robotics, segmentation, simulation, tensorflow
• Language: Jupyter Notebook
• Homepage:
• Size: 128 MB
• Stars: 7
• Watchers: 2
• Forks: 6
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
## Deep Learning Drone Simulator ##

[image_0]: ./docs/misc/sim_screenshot.png

![alt text][image_0] 

This [Udacity clone project](https://github.com/udacity/RoboND-DeepLearning.git)  is to  learn  how to build a neural network

 and how all the individual pieces function together to form a powerful decision-making drone machine.

**TensorFlow**  which is a robust software framework developed by Google to facilitate building deep neural networks is 

used to abstract away many of the finer details and make life easier are used in this project. However, it is important 

to have a firm grasp of the fundamentals to understand the choices needed to make in setting various parameters or 

how to improve the performance of the neural network.

## Wiki Content

1. [**What is Deep Learning?**](https://github.com/fouliex/DeepLearningDroneSimulator/wiki/1.-What-is-Deep-Learning%3F)

2. [**Segmentation Network Implementation and Architecture**](https://github.com/fouliex/DeepLearningDroneSimulator/wiki/2.-The-Segmentation-Network-and-Architecture)

3. [**Setup Instructions**](https://github.com/fouliex/DeepLearningDroneSimulator/wiki/3.-Setup-Instructions)

4. [**Data Collection**](https://github.com/fouliex/DeepLearningDroneSimulator/wiki/4-.-Data-Collection)

5. [**Results, Limitations and Future Enhancements**](https://github.com/fouliex/DeepLearningDroneSimulator/wiki/5.-Results-and-Limitations) 

6. [**Testing in Simulation**](https://github.com/fouliex/DeepLearningDroneSimulator/wiki/6.-Testing-in-Simulation)

[image_1]: ./misc/FollowMeGif.gif

![alt text][image_1]