Automatic Target Detection
Automatic Target Detection is basically a quad copter system in which we have given the data of a specific Object. By using the raspberry pi real time video streaming. The video will be detected in the raspberry pi, afterwards a command will be sent to Arduino using MAVLink. After matching the image
2025-06-28 16:30:29 - Adil Khan
Automatic Target Detection
Project Area of Specialization RoboticsProject SummaryAutomatic Target Detection is basically a quad copter system in which we have given the data of a specific Object. By using the raspberry pi real time video streaming. The video will be detected in the raspberry pi, afterwards a command will be sent to Arduino using MAVLink. After matching the images with the pre-defined dataset, the quad copter will take further action to settle onto the target. The Quadcopter consists of four brushless motors each of them connected with a separate electronic speed controller (ESC) connected with a 3-cell lithium battery.
The quadcopter system is an extremely maneuverable and versatile platform for many applications especially surveillance which can be used to monitor and survey important areas as well as areas which are normally very difficult to access or dangerous locations. The main objective of this project is to create an autonomous quadcopter for surveillance through camera and to search and retrieve the information about surrounding environment. This drone can be used for agriculture, military applications, disaster relief.
Project ObjectivesThe objectives of Automatic Target Detection are as follows:
- To detect the desired target image.
- After detecting the desired image, the quadcopter will make a decision using Pixhawk.
- The quadcopter will decide to settle on the desired target.
In addition to this, Raspberry Pi Model 3B+ will be used for the desired targeted object detection. The detection of the object will be done via live streaming. After detection, the command will be sent from serial port of the Raspberry Pi to the Arudino nano and the Arudino nano will forward the command to the Pixhawk using MAVLink.
Project Implementation MethodThe implementation of Automatic Target Detection is as follows:
- Installing the Raspbian OS in Raspberry Pi.
- Installing the OpenCV in Raspberry Pi.
- Installing the Mission Planner Software.
- Calibration of PixHawk Flight Controller.
- Assembling the hardware of quadcopter.
- Testing the quadcopter using RC (Remote Control).
- Autonomous testing of the quadcopter flight testing.
- Image Detection of object using opencv
The benefits of Automatic Target Detection are as follows:
- Lost Object Survelliance
- Accident Location Survelliance
- Military Target Survelliance
- First Aid Purpose
- Rapid Fast Food Delivery
At the end of this project, the quadcopter will be deployed for the military organizations.
Final Deliverable of the Project Hardware SystemType of Industry IT , Security Technologies Robotics, OthersSustainable Development Goals Industry, Innovation and InfrastructureRequired Resources| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Total in (Rs) | 70000 | |||
| Raspberry Pi 3 B+ | Equipment | 1 | 8500 | 8500 |
| Raspberry Pi 3 B+ Body | Equipment | 1 | 500 | 500 |
| Arduino Nano | Equipment | 1 | 500 | 500 |
| Brushless Motor LC-3536 960kV | Equipment | 4 | 4000 | 16000 |
| ESC (Electronic Speed Controller) | Equipment | 4 | 2800 | 11200 |
| Pixhawk 2.4.8 (Flight Controller) | Equipment | 1 | 8000 | 8000 |
| Mania X 3300 mAh Battery | Equipment | 1 | 8000 | 8000 |
| S500 PCB Frame Kit | Equipment | 1 | 7500 | 7500 |
| Pixhawk GPS Module | Equipment | 1 | 3500 | 3500 |
| 3DR Power Module | Equipment | 1 | 2000 | 2000 |
| 12inch Propeller | Equipment | 4 | 275 | 1100 |
| Radio Telemetry Kit | Equipment | 1 | 3200 | 3200 |