MUMBAI, India, Sept. 22 -- Intellectual Property India has published a patent application (202641109896 A) filed by R. M. K. Engineering College on September 14, 2026, for Development Of An Autonomous Agricultural Ploughing Machine Using Micro-Ros, Gps Mapping, And Computer Vision.
Inventors include Hakesh K; Prashad Sivalingam; Dhanush Rajan B; and Dr. S. D. Sekar.
The application for the patent was published on September 18, 2026, under issue no. 38/2026.
Abstract: The present invention relates to an autonomous agricultural ploughing machine integrating Micro-ROS, GPS-based navigation, motor control, and computer vision for efficient, accurate, and safe soil preparation. The system is designed to reduce manual intervention, operational time, labor dependency, and the cost associated with conventional agricultural machinery. A microcontroller operating with Micro-ROS communicates with a master computing system to receive navigation information generated from GPS-based field mapping. The master computing system determines the geographical coordinates and predefined ploughing path of the agricultural field, which are transmitted to the microcontroller for controlling the drive motors and enabling autonomous navigation along the designated path. Further, a camera module continuously captures the surrounding field environment, and the acquired images or video are processed using OpenCV and a YOLO-based object detection model to identify potential obstacles, including humans, animals, rocks, and other objects. Upon detection of an obstacle within the operating path, the control system automatically pauses the machine and permits continuation of the ploughing operation after the path is determined to be clear. The integration of lightweight Micro- ROS-based control with GPS navigation and real-time computer vision provides a cost-effective, scalable, and intelligent solution for autonomous agricultural operations. The proposed invention enhances navigation accuracy, operational safety, and consistency of soil preparation while reducing dependence on high-end onboard computing hardware, thereby supporting the development of precision agriculture and smart farming systems.
Disclaimer: Curated by HT Syndication.
