Agriculture is one of the areas that can benefit from robotics technology, as it faces issues such as a shortage of human labor and access to less arid terrain. Harvesting is an important step in agriculture since workers are required to work around the clock. The red ripe tomatoes should go to the nearest market, while the greenest should go to the farthest market. Harvesting robots can benefit from Neural Network-based image processing to ensure robust detection. The vision system should assist the mobility system in moving precisely and at the appropriate speed. The design and implementation of a harvesting robot are described in this study. The efficiency of the proposed strategy is tested by picking red-ripened tomatoes while leaving the yellowish ones out of the experimental test bed. The experiment results demonstrate that the effectiveness of the proposed method in harvesting the right tomatoes is 80%.
Copyrights © 2023