Currently, there are significant challenges faced by the farming industry, which are a reduction in the available labour workforce, and a more 'corporate' style of farming. So such factors demand an increase in farming efficiency and productivity. In this regard, Autonomous Agriculture is seen as an effective tool for bringing together the areas of robotics, embedded systems and precision agriculture (PA) which not only deals with issues of agronomy but also provides better technology like “On-farm sensing and control” to actuate autonomous farm machinery for better farm management. It is a system-of-systems architecture, or unified framework, where a vital building block is the existence of two data sets used as links, or communication, between the various sub-systems. These data sets include a precision farming data set (PFDS) containing spatially precise navigation data (like how healthy is crop, map yield, moisture data, temperature, humidity etc.) for all autonomous machinery, and a precision agriculture data set (PADS), which is a continually evolving entity consisting more of agronomy data in relation to the crop for better sustenance, productivity and yield of the crop.