In this paper, the design, implantation, and testing of an autonomous agricultural robot with GPS guidance is presented. This robot is also responsible for weed detection and killing by spraying appropriate herbicide as well as fertilizing. This rover is powered by 5 12V electric bike batteries and two electric motors. Machine learning algorithms such as Haar Cascade has been successfully utilized to detect three kind of common weeds found in a corn field. The robot control system consists of GPS guided control of propulsion system and steering actuators, an image processing and detection system, and an spray control system for herbicide and fertilizer applications. Multiple microprocessors such as Raspberry Pi 3, Arduino, as well as an on-board computer have used to provide all control functions in an integrated fashion. Open sources software such as Mission Planner and ReachView have been used to provide autonomous guidance of the vehicle. This vehicle successfully participated in 2017 AgBot Challenge where it traversed the corn field autonomously which detecting and killing weeds with certain degree of accuracy and applying fertilizer. The test results are very promising and are shown in this paper.