Agriculture and labor saving in agriculture is in the need of modern era. However, mechanization for fruit harvesting has not been advanced yet. This project proposes a method of detecting fruits and automated harvesting using a robotic arm by digital image processing.A highly fast and accurate meth
Automated Fruit Harvesting Robot
Agriculture and labor saving in agriculture is in the need of modern era. However, mechanization for fruit harvesting has not been advanced yet. This project proposes a method of detecting fruits and automated harvesting using a robotic arm by digital image processing.A highly fast and accurate method with a Single Shot MultiBox Detector will be used to detect the position of fruit, and a stereo camera to detect the two-dimensional position. The stereo camera will be attached to the gripper tool in order to obtain relative distance,orientation and size of the fruit. The harvesting stage requires the initial fruit location,the computation of the inverse kinematics of the robotic arm in order to place the gripper tool in front of the fruit, and a final pickup approach.After calculating the angles of the joints at the detected position by inverse kinematics, the robot arm will move to the target fruit’s position. The robot will then harvest the fruit by twisting the hand axis.
The major objectives of our project are:
•The development of automatic systems that replace manpower in tasks while a person performs worse than an automatic device in terms of precision, repetitivity and working cycle
•To reduce the labor as well as cost
•To save the time and increase the accuracy
•To do effiecient work
And talking about our country which is a agro-based country and our whole economy depends on our agriculture. But if we look at our agricultural technology which is not still much advanced and the fruits are still picked manually. Manual picking of fruits is not so effecient and requires more time and labor so why not replacing the labor with technology and get the work done effeciently.

looked up from directly below.We will use universal robot as the robotic arm. The location of the fruits will be performed by matching fruit centroids instead of matching the complete stereo-image as a way to reduce matching complexity algorithm and foster the future development of real-time industrial systems.
Single Shot MultiBox Detector (SSD) to detect the two dimensional (2D) position of the fruit. SSD is one of the general object detection methods. SSD can comprehensively judge from color and shape. SSD speeds up the process by eliminating the need for the region proposal network. To recover the drop in accuracy, SSD applies a few improvements including multi-scale features and default boxes. SSD also detects 3D the position of fruits by measuring the angles.
The control of the robotic arm requires an estimate of the fruit distances,positions and sizes in the trees in order to
propose an automatic fruit harvesting procedure. A three-dimensional (3D) position will be obtained to send a command to the robot arm. A stereo camera will be used to measure the 3D position of the fruit detected by the SSD.
There are very tangible benefits of robotics on modern agriculture for producers and consumers alike. Some of the most significant benefits are:
Decreased cost of production;
Information sharing between producers and consumers;
Improved supply chain;
Increased labor efficiency and decreased cost;
Reduced food wastage and increased yields;
Increased financial sustainability.
Our final prototype of fruit harvesting robot will successfully pick the fruits with full accuracy of more than 90% and with a time less than 15 seconds.
Final Deliverable will be a robotic arm,which will be controlled by giving output through LCD.
The user will give input to the system that he wants to pick the red apples only, and then the system will check its database and by using machine learning,it'll gve instructions to the robotic arm to pick the red apples from the tree in real time. This project is a industrial level project and it has great innovation of picking multiple fruits in real time. We'll use python coding.
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Raspbeery pi 4 | Equipment | 1 | 25500 | 25500 |
| Raspberry pi camera | Equipment | 1 | 9000 | 9000 |
| ESP32 | Equipment | 1 | 850 | 850 |
| L298n motor driver | Equipment | 1 | 320 | 320 |
| Ultrasonic sensor | Equipment | 2 | 200 | 400 |
| Car kit | Equipment | 1 | 440 | 440 |
| 775 DC motors | Equipment | 4 | 550 | 2200 |
| Servo motors | Equipment | 5 | 750 | 3750 |
| Battery 3.7V 2200mah | Equipment | 8 | 190 | 1520 |
| Battery charging module | Equipment | 2 | 60 | 120 |
| Battery holder | Equipment | 2 | 140 | 280 |
| Buzzer | Equipment | 1 | 150 | 150 |
| Buck converter | Miscellaneous | 2 | 740 | 1480 |
| Robotic Arm kit | Equipment | 1 | 1550 | 1550 |
| OLED 1.9inch display | Equipment | 1 | 500 | 500 |
| MOSFET | Miscellaneous | 4 | 50 | 200 |
| NPN transistor | Miscellaneous | 4 | 30 | 120 |
| LED Mix colors | Equipment | 20 | 230 | 4600 |
| Resistors | Miscellaneous | 30 | 20 | 600 |
| Capacitor | Miscellaneous | 10 | 20 | 200 |
| Switch | Miscellaneous | 1 | 150 | 150 |
| Charger | Equipment | 1 | 250 | 250 |
| LDR | Miscellaneous | 1 | 100 | 100 |
| Charging connectors | Equipment | 2 | 80 | 160 |
| Wires | Miscellaneous | 40 | 10 | 400 |
| 3.3V regulator | Miscellaneous | 2 | 25 | 50 |
| IR LED Transmitter | Miscellaneous | 4 | 20 | 80 |
| Photo Diode | Miscellaneous | 2 | 250 | 500 |
| Total in (Rs) | 55470 |
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