DESIGN AND FABRICATION OF THE AUTONOMOUS FRUIT PLUCKING ROBOT

Advait Patole, Jeet Acharya

Abstract


The people of India are mainly dependent on the agriculture and allied field. In order to alleviate the crisis on farming fronts, it is necessary that we should discover new mechanisms by which farmers are adequately and rightfully compensated for their labour. That is the reason why an autonomous robot had to be made in order to reduce the labour and labour costs of farming in India. Fruit plucking is an important process in farming. An autonomous robot which could pluck fruits on its own in a farm would be the best possible alternative of manual labour for plucking fruits in a farm. Such a fruit plucking robot can move autonomously in a farm containing plantations of a given fruit using placards or signs placed at each plant bearing that particular fruit. After detecting the actual fruit using image processing, it can operate its links of the robotic arm to reach the particular fruit. After reaching the fruit, it can pluck the fruit using the plucking mechanism. This whole process can be done by a single robot autonomously which can be released in the farm to perform the fruit plucking process. It provides an excellent substitute of manual labour for performing the plucking process in agricultural fields.

Keywords


robotic arm, hough circle transform, OpenCV DNN, inverse kinematics, pixel to co-ordinate conversion, serial communication

Full Text:

PDF

References


Roy, S. (2019). Real-Time Object Detection on Raspberry Pi Using OpenCV DNN. Retrieved from https://heartbeat.fritz.ai/real-time-object-detection-on-raspberry-pi-using-opencv-dnn-98827255fa60

Lv, J., Yang, F., Shen, G., & Ma, Z. (2019). Research on trunk and branch recognition method of apple harvesting robot - IEEE Conference Publication. Retrieved from https://ieeexplore.ieee.org/document/6273345

R-CNN, Fast R-CNN, Faster R-CNN, YOLO — Object Detection Algorithms. (2019). Retrieved from https://towardsdatascience.com/r-cnn-fast-r-cnn-faster-r-cnn-yolo-object-detection-algorithms-36d53571365e

Raffin, A. Simple and Robust {Computer — Arduino} Serial Communication. Retrieved fromhttps://medium.com/@araffin/simple-and-robust-computer-arduino-serial-communication-f91b95596788

Traffic light and sign detection for autonomous land vehicle using Raspberry Pi - IEEE ConferencePublication. (2017). Retrieved from https://ieeexplore.ieee.org/document/8365328

Lau, B. Andrew Ng’s Machine Learning Course in Python (Kmeans-Clustering, PCA). Retrieved from https://towardsdatascience.com/andrew-ngs-machine-learning-course-in-python-kmeans-clustering-pca-b7ba6fafa74

Hough Line Transform — OpenCV 3.0.0-dev documentation. Retrieved from https://docs.opencv.org/3.0-beta/doc/py_tutorials/py_imgproc/py_houghlines/py_houghlines.html


Refbacks

  • There are currently no refbacks.




Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Copyright © 2019 INTERNATIONAL EDUCATION AND RESEARCH JOURNAL