The project is based on AI OpenCV Neural Network which will alow the Robotic CAR it self to operate in real time environment. The Robotic CAR will be able to reach its destination from the source, keeping all the necessary environmental conditions in view. It will adjust it s
Automated Car
The project is based on AI OpenCV Neural Network which will alow the Robotic CAR it self to operate in real time environment. The Robotic CAR will be able to reach its destination from the source, keeping all the necessary environmental conditions in view.
This project will consits of three main subsystems:
The objectives of the this project are as following:
Algorithms and techniques that we will need to accomplish this system are
Project Implementation Method
This system or prototype is divided into three sub-systems
1- Input Unit
Input unit includes Raspberry Pi board (model B+), attached with a pi camera module and different sensors are used to collect input data. Client program run on Raspberry Pi for streaming colour video. In order to achieve low latency video streaming, video can be scaled down to 320×240 resolution.
2- Processing Unit
The processing unit (computer) will handle multiple tasks like receiving data from Raspberry Pi, neural network training and prediction (steering), object detection (stop sign and traffic light), distance measurement (monocular vision), and sending instructions to Arduino through USB connection.
3- Control Unit
The prototype that we will use in this project will have an on/off switch type controller. When a button is pressed, the resistance between the relevant chip pin and ground is zero. Thus, an Arduino board is used to simulate button-press actions. Arduino pins will be used to connect four chip pins on the controller, corresponding to forward, reverse, left and right actions respectively. Arduino pins sending LOW signal indicates grounding the chip pins of the controller, on the other hand sending HIGH signal indicates the resistance between chip pins and ground remain unchanged. The Arduino is connected to the computer via USB. The computer will output commands to Arduino using serial interface, and then the Arduino will read the commands and writes out LOW or HIGH signals, simulating button-press actions to drive the prototype.
Benefits of the Project
Resource Requirement
Tools / Technology
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Raspberry Pi 4 (4GB RAM) | Equipment | 1 | 17500 | 17500 |
| Raspberry Pi Heatsink Cooler | Miscellaneous | 1 | 150 | 150 |
| Raspberry Pi 4 HDMI Cable | Equipment | 1 | 300 | 300 |
| 8MP Raspberry Pi Camera Module V2 | Equipment | 1 | 4800 | 4800 |
| Class 10 SanDisk 32GB Ultra Micro SD Card | Equipment | 1 | 1500 | 1500 |
| Raspberry Pi 4 Case with fan fitting | Miscellaneous | 1 | 350 | 350 |
| 10000mAH PowerBank | Equipment | 1 | 2500 | 2500 |
| Arduino Uno R3 with cable | Equipment | 1 | 800 | 800 |
| IR infrared obstacle avoidance sensor | Equipment | 4 | 100 | 400 |
| Ultrasonic Sensor | Equipment | 4 | 150 | 600 |
| 4WD smart robot car chassis kit | Equipment | 1 | 1300 | 1300 |
| TCRT 5000 line tracking sensor module | Equipment | 2 | 100 | 200 |
| L293D Motor Driver Shield | Equipment | 1 | 400 | 400 |
| Traffic Light LED Module | Equipment | 1 | 100 | 100 |
| Jumping Wires (M-M, M-F) | Miscellaneous | 2 | 200 | 400 |
| Card Board Sheet 4x4 | Miscellaneous | 6 | 160 | 960 |
| Chart Papers (White and Black) | Miscellaneous | 10 | 20 | 200 |
| Total in (Rs) | 32460 |
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