Abstract
This research letter describes an autonomous agricultural mobile robot for weeding operations in agricultural fields in the Almaty region of Kazakhstan. The development of such robots has the potential to revolutionize the agricultural industry by reducing the need for herbicides and manual labor. Machine learning algorithms are trained to identify various types of weeds, and the robots are programmed to selectively remove them without damaging crops. The use of these robots can lead to increased efficiency, decreased costs, and improved environmental sustainability in agriculture. Moreover, this research describes the use of ML for weed recognition and precise killing by pesticides. The research paper is organized in the following order; introduction, robot design, robot control system, and weed recognition system.