Precision agriculture makes use of high-accuracy navigation, attitude determination, and obstacle detection methods to save resources and to obtain better results. The collected robot position and attitude, and obstacle location data can be effectively employed to synthesize control algorithms for autonomous agricultural machines. These algorithms are applied for coverage path planning, route planning, motion stabilization along the specified paths, obstacle avoidance, and ensuring guaranteed behavior. These tasks are considered in the paper.