<![CDATA[This study designs, implements, and evaluates an autonomous robotic weeding system as a mechanical solution to reduce herbicide dependence in organic vegetable farming. Organic farming faces persistent weed management challenges due to restrictions on synthetic herbicides and rising labor costs. Weeds compete with crops for essential resources, resulting in yield losses and reduced efficiency. While mechanical weeding has been a viable alternative, traditional methods often lack precision and can harm crops. Recent advances in robotics and automation offer a solution by enabling intelligent, autonomous weed control that aligns with sustainable agricultural practices. The research uses a design-and-experimental methodology, developing an autonomous robotic platform equipped with vision-based sensors, navigation algorithms, and mechanical weeding tools. The system was tested in organic vegetable plots, and field trials measured weed removal efficiency, crop safety, operational accuracy, and energy consumption, with comparisons to traditional manual weeding methods. The results showed that the robotic system effectively reduced weed density with high precision while minimizing crop disturbance. The system demonstrated consistent performance across test plots and significantly reduced reliance on manual labor and chemical inputs. Weed control efficiency was comparable to traditional methods, with improved consistency and reduced operational fatigue. The study concludes that robotic weeding is a viable, sustainable solution for weed management in organic vegetable farming and offers promising implications for smart agriculture and technology-integrated education. ]]>
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