Agricultural production is a key economic activity providing a growing world population with resources like food, fibers, fuels, and chemical basic components. Yet, agriculture also plays a crucial role in the depletion of resources like fresh water, fossil fuels, and nutrients (e.g., phosphate) and has a significant impact on our living environment through emissions and the use of chemicals. Despite a growing world population, labor participation in agricultural production is declining. Technology has been instrumental in the very successful development of agriculture throughout the centuries and will play a crucial role in the European Green Deal that addresses the transition to a more sustainable agri-food production in the years that lay ahead of us. It is expected that technologies like Artificial Intelligence, Data, and Robotics will be leading in this transition. During this transition, it is critically important to support agri-food production with novel technologies. Covering the value chain from breeding, through on-farm production, post-harvest storage, logistics, packaging, and food processing, the agri-food production network is an ecosystem providing agri-food products and services. Besides food, other off-farm productions do exist including harvesting of wild food, fisheries, indoor farming, both large scale commercial, and home growing, forestry, and, last but not least, urban landscaping and maintenance where robot technologies can and will be applied as well. The current release of this agenda mainly focuses on the food production part. Being a working document, the authors wish to express the hope that it will serve as a basis for further elaboration to encompass the whole agrifood domain in its full width and depth. With an emphasis on robotics and to a lesser extent on AI and Data, this report provides a vision and mission on what robotics should contribute and how to facilitate the transition to a more sustainable agri-food production. Key challenges in terms of technology, ecosystem, and market are derived from 12 use-case themes within the agri-food production domain. Use-case themes represent classes of functionality that go beyond specific individual applications and application domains. Despite of aiming to identify high-level cross-domain challenges in robotics, AI, and Data agri-food and offering the opportunity to connect to other technical and application domains, this classification is not considered to be exhaustive.