Semantic Robots

The Semantic Robots research profile employs a dozen post-docs and senior researchers at AASS, and involves tight collaborations with major Swedish industrial partners. Its objective is to create sustainable world-class research at AASS in the area of Robotics and AI. Research activities are grounded on industrial case-studies elicited from major Swedish companies.

Funders: The Swedish Knowledge Foundation (KKS), Örebro University

Partners: Epiroc, Volvo Construction Equipment, Volvo Trucks, Husqvarna, Kollmorgen Automation, Saab, CNet, Fotonic


The aim of this project is to develop AI-based software tools for automated online Load-Haul-Dump planning in underground mines. The objective is to render mining operations more flexible and effective. This is achieved via a combination of automated planning, optimization and multi-robot coordination algorithms.

Funder: Vinnova, Swedish Mining Innovation program

Partners: Örebro Unievrsity, Epiroc, Newcrest Mining Pty Ltd 


The project seeks to generalize the multi-robot planning and control developed in the lab to robot arms and, eventually, mobile manipulators. The project is centered on a use-case in underground mining, where the manipulators to be coordinated are multi-jointed drilling booms. A research platform consisting of three Franka Emika Pandas was built as a development platform.

Funder: Vinnova, Swedish Mining Innovation program

Partners: Örebro Unievrsity, Epiroc, ZinkGruvan Mining, Alfred Nobel Science Park


The iQMobility project deals with developing fleets of autonomous buses. The project is led by Scania and also involves KTH and the company INIT. Our role in the project is to develop motion planning and coordination algorithms for use in automated bus depots, with the specific challenge of integrating motion planning and coordination.

Funder: Vinnova, Strategic vehicle research and innovation programme (FFI)

Partners: Scania, Örebro University, KTH, INIT


ILIAD aims to develop highly flexible, rock-solid reliable, self-optimizing, quickly deployable, safe and efficient warehouse automation solutions. Our lab leads the workpackage dealing with automated fleet management, and collaborates with partners to develop integrated coordination, motion planning and control methods for fleets of autonomous forklifts.

Funder: EU H2020

Partners: Örebro University, University of Lincoln, University of Pisa, Technical University of Munich, Bosch, Kollmorgen Automation, ACT Operations Research, Orkla Foods Sverige, Logistic Engineering Services


In January 2019, the AI4EU consortium was established to build the first European Artificial Intelligence On-Demand Platform and Ecosystem with the support of the European Commission under the H2020 programme. The project supports research and road-mapping activities in five key areas arising from the application of AI in real-world scenarios, namely, Explainable AI, Physical AI ,Verifiable AI, Collaborative AI, and Integrative AI. The Multi-Robot Planning and Control lab is involved mainly in the area of Integrative AI. The lab has also contributed the Meta-CSP framework and the coordination_oru library to the AI4EU platform

Funder: EU H2020

Partners: please see project fact sheet on Cordis.

ML to enhance AI Planning for Intelligent Transport Systems

AI planning and scheduling methods are fundamental in industrial transport applications, automating key stages in the overall process of assigning tasks and ensuring that plans remain feasible over time. These methods typically rely on manually-specified knowledge to derive plans, many aspects of which are only known to human planning experts (e.g., impenetrable forest roads, icy terrain, etc). This project aims to enhanced AI planning and scheduling methods with the ability to learn from human planning experts and from experience. The primary class of use-cases for this project is that of autonomous transport domains.

Funder: Swedish Foundation for Strategic Research (SSF)

Partners: Örebro University, Scania


The AIPlan4EU project aims to bring AI planning into the European AI On-Demand (AI4EU) Platform. The project will integrate state of the art automated planning systems into an API that can be used to realize automated decision-making solutions for the industry. The project is driven by use-cases provided by industrial actors. AIPlan4EU also provides cascade funding aimed at integrating new use cases as well as new planning engines.

Funder: EU H2020

Partners: please see project website.