Steering Control of Ackermann Architecture Weed Managing Mobile Robot
Journal Title: International Journal of Innovations in Science and Technology - Year 2025, Vol 7, Issue 5
Abstract
A robot designed to identify and remove weeds from crops is known as a weed control robot. Weeds compete with primary crops for moisture, hinder their growth, and may harm both human and animal health, leading to reduced crop yields. Traditionally, herbicides and other chemicals have been used to eliminate weeds, but these methods can damage crops and pollute the environment. In this work, we propose a new semantic weed detection method based on the PC/BC-DIM network, which demonstrates superior performance and classification accuracy compared to existing approaches. We developed an autonomous weed control robot incorporating Ackermann Architecture and a delta robot. The delta robot is equipped with a camera at its base to detect weeds in real-time. First, the robot captures images using the camera, and through image processing techniques, it differentiates weeds from crops. Detected weeds are then eliminated using an electrical discharge method, where electrodes attached to the robot’s end effector burn the targeted weeds. Additionally, we developed a path-planning and obstacle-avoidance system to help the mobile robot navigate the field. This system uses stereo vision to capture stereo images of the environment and calculate their disparity. By extracting depth information, the robot can detect obstacles, avoid them, and follow the shortest path using the A* algorithm. The results from this work are simulation-based, demonstrating effective weed detection in field images and efficient robot navigation using stereo images. The system achieved an overall accuracy of 81.25%. Although the system performs moderately well, the relatively high False Positive Rate and Root Mean Square (RMS) Error indicate the need for further improvements to reduce errors and false positives. Future work will focus on enhancing weed removal and implementing the simulated results on hardware.
Authors and Affiliations
Faryal Naeem Mehmood, Syeda Ambreen Zahra, Syed Muhammad Wasif, Zubair Mehmood, Muhammad Jehanzeb Irshad, Nazam Siddique
Keywords
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- EP ID EP764472
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