About this project
Today, intralogistic services have to respond quickly to changing market needs, unforeseeable trends and shorter product life cycles. These drivers pose new demands on intralogistic systems to be highly flexible, rock-solid reliable, self-optimising, quickly deployable and safe yet efficient in environments shared with humans.
The aim of the ILIAD research project was to enable the transition to automation of intralogistic services with key stakeholders from the food distribution sector, where these challenges are particularly pressing. The particpants in ILIAD have developed robotic solutions that can integrate with current warehouse facilities, extending the state of the art to achieve self-deploying fleets of heterogeneous robots in multiple-actor systems; life-long self-optimisation; manipulation from a mobile platform; efficient and safe operation in environments shared with humans; and efficient fleet management with formal guarantees.
Scientifically, ILIAD has pursued ambitious goals for complex cognitive systems in human environments beyond a specific use-case. Goals was to overcome limitations in the state of the art in tracking and analysing humans; quantifying map quality and predicting future states depending on activity patterns inferred from long-term observations; planning of socially normative movements using learned human models; integration of task allocation, coordination and motion planning for heterogeneous robot fleets; and systematically studying human safety in mixed environments, providing a foundation for future safety standards.