== **Self-Driving Vehicular Project**\\

**Team**: Aaron Cruz [UG], Arya Shetty [UG], Brandon Cheng [UG], Tommy Chu [UG], Vineal Sunkara [UG], Divya Krishna [HS], Siddarth Malhotra [HS]

**Advisors**:  Ivan Seskar and Jennifer Shane


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**Project Description & Goals**:\\
Build and train miniature autonomous cars to drive in a miniature city. \\
RASCAL (Robotic Autonomous Scale Car for Adaptive Learning): Using the car sensors, offload image and control data onto a server node. This node will use a neural network that will train the vehicle to move around on its own given the image data it sees through its camera.\\

 
[[Image(gitlab.png, 500px)]] [[Image(SDC Week 2.png, 690px)]]\\

[https://gitlab.orbit-lab.org/self-driving-car-2023/ GitLab]


**Technologies**: ROS (Robot Operating System), Pytorch


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**Week 1**:\\

[https://docs.google.com/presentation/d/1_K0UlIok6UAKQ4FFww5lPMrha5UKXG6zL87LEalwGbc/edit? Week 1 Slides]


Progress:
- Familiarize with past summer's work:[https://gitlab.orbit-lab.org/self-driving-car-2023/upcar GitLab], RASCAL setup, [https://www.orbit-lab.org/attachment/wiki/Other/Summer/2023/OH2023/P10a.jpg Software Architecture]
- Debug issue with RASCAL's pure pursuit

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**Week 2**:\\

[https://docs.google.com/presentation/d/1-SxxC-grfdlDhFj4ZKn8_SqMMATA9l2CJ__-rpB7mYw/edit?usp=sharing Week 2 Slides]

Progress:
- Setup X11 forwarding for GUI applications through SSH
- Visual odometry using Realsense Camera and [https://wiki.ros.org/rtabmap_ros/TutorialsOldInterface/StereoHandHeldMapping#Bring-up_example_with_RealSense_cameras rtabmap]
- Streamline data pipeline that processes bag data (car camera + control data) into .mp4 video
- Detect ARUCO markers from a given image using Python & OpenCV libraries
- Setup Intersection server (node with GPU)
- Develop PyTorch MNIST model
- Trained "yellow thing" neural network 
- Line up perspective drawing with camera to determine FOV
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**Week 3**:\\

[Week 3 Slides]

Progress:
- Created web display assassin to eliminate web server when closing ROS
- Tested "yellow thing" model, great results 
- SSHFS setup
- Calibrate Real Sense camera
- Created "snap picture" button on web display for convenience
- Developed python script to detect ARUCO marker and estimate camera position

[[Image(Detected.png, 500px)]]

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