Fernando Auat Cheein

UK National Robotarium, Edinburgh Centre for Robotics

School of Engineering and Physical Sciences, Heriot-Watt University

EH14 4AS, Edinburgh, UK,

Agricultural processes are currently attracting the attention of the Industry 4.0 revolution. From a process historically left behind in technologization, agriculture is experiencing strong investment from private and government, aimed at improving efficiency not only in what concerns to resource management, but also in the compensation of the lack of human labor force. The later is a problem faced in most developed countries, but also in third world countries: new generations are not taking the field work left by former generations, since cities or other industrial sectors offer more attractive jobs and salaries. This situation presents a problem, considering the world ever increasing population. To fully understand the problem, this presentation is aimed at showing the different issues yet to be faced to have a fully automated agricultural process, with special focus on fruit orchards. The presentation covers the most recent developments in agricultural machinery for orchard management, including pruning, harvesting, herbicide handling, among others, aided by the perception techniques which are benefited from machine learning tools. The presentation is supported by several case studies covering international agricultural practices.