In this project, we seek to create a closed-loop system for managing manure of grazing livestock. To accomplish this goal, we will use a autonomous vehicle platform which will work collaboratively with sensors on livestock in the field. Livestock sensors will flag where and when animal defecate and urinate within the field and send this information to the autonomous vehicle. The vehicle will then plan and execute a manure management strategy based on the location of manure in the field and sensed data describing the moisture and nutrient composition of the pasture soil. Manure management options will include moving manure to different areas of the field that have more faborable nutrient composition or are less hydrologically sensitive; tiling manure into the soil to prevent surface runoff; and removing manure from the field entirely. Through these management options, they system will precision-manage the nutrient composition of soil to optimize manure value as fertilizer and minimize environmental impacts. In order to work toward this vision, we will also conduct a number of addiitonal tests, including evaluating the animal-robot interactions within the field; leveraging novel simulation platforms to efficiently train autoonomous control approaches; and development work to improve precision and accuracy of sensors to detect soil nutrient compostion. Collectively, these investigations will contribute to our efforts to generate the resultant closed-loop system which we will then demonstrate on research and working farms.