Autonomous Mobile Machines Group

An European Industrial Doctoral Network: Educating Europe`s Future Engineers for the Next Generation of Mobile Working Machines: AI driven Sustainability, Productivity, and Safety

This profiling area concentrates on creating new communication and sensor technology and the corresponding advanced SoCs, with specific emphasis on the intelligent mobile working machine. Our aim is to make future machines increasingly autonomous, energy-efficient, cost-efficient, and safe.

The target of Aurora co-innovation project is to research technologies required in the field of heavy machine automation, applicable to wide range of industries, such as, forest machines, cargo handling solutions, mining related machines and excavators, just to name a few. Research will especially focus on combining advanced sensing and control methods with state-of-the-art radio-based technologies. Project results can be generalized and utilized also in other fields where, for example, robust wireless sensing and control is needed.

Heavy machinery is often used in harsh environments, such as excavations, forests or urban traffic in northern weather conditions. Self-driving vehicles need to operate on icy roads in winter, and excavators need to be able to cope on terrain with loose soil. All kinds of unpredictable environmental conditions – such as ice, snow, mud and unmovable large rocks – make the use of self-driving technology difficult and dangerous, as an autonomous vehicle may not be able to cope with rapid and unpredictable changes in the weather. An international team of researchers from Academy and Industry will look for AI-based ways to ensure the safety and reliability of self-driving heavy vehicles in such conditions. The aim of the project is to improve autonomous operations in land management, forestry and logistics to reduce the fuel consumption of vehicles and environmental impacts such as soil damage.

Intelligent mobile machines (operator assistance, semi-autonomous, teleoperations, autonomous) rely on multimodal sensors such as cameras, lidars, radars, IMUs, and GNSS. Since these sensors provide different types of data, they need to be well calibrated for safe and productive operations. The SenCAN project investigates the commercialization potential of the sensor-to-sensor calibration solutions which are developed and used within our research group. The SenCAN project has received the Research to Business (R2B) funding from Business Finland. Thus, the main aim of SenCAN is to bring “Automated sensor calibration” to Intelligent MWMs. The target applications are mobile machinery used within agriculture, forestry, construction, mining, and yard logistics.

Europe needs an open-source ecosystem to drive competitiveness and enable more agile innovation. Using open-source hardware and software drastically lowers the barrier to designing innovative integrated circuits. The KDT-JU-funded TRISTAN project aims to expand and develop RISC-V architecture in Europe to compete with existing commercial alternatives. This open specification eliminates the need to learn and create unique ecosystems for each processor architecture, increasing productivity, security and transparency. TRISTAN’s approach will be holistic, covering electronic design automation tools and the full software stack. TRISTAN’S overarching aim is to expand, mature and industrialize the European RISC-V ecosystem to compete with existing commercial alternatives. Building blocks developed in TRISTAN will be demonstrated in the business domains of Automotive, Industrial, Aerospace, Mobile, Wearables and Health.

The Finnish Doctoral Program Network in Artificial Intelligence launched in 2024 to build a world-class PhD program with quality supervision, mobility, and multi-disciplinarity as integral parts. The program is a joint effort of to educate 100 new PhDs in artificial intelligence research. Finland’s Ministry of Education and Culture has granted 25.5 million EUR to support the program. The group has one doctoral student on "Advanced Learning of Safe Autonomous Navigation on Rough Terrain".

SustAInLivWork – a Centre of Excellence for Sustainable Living and Working, specialized in the development and application of R&I solutions based on Artificial Intelligence in the manufacturing, energy, health and transport sectors. This Centre of Excellence will act as a lighthouse with far reaching impact strengthening R&I in the national and international scope, nurturing from a cooperation between key national partners. TAU acts as advanced partner in the project, and our group has significant contribution from TAU side.

AI Hub Tampere is a regional hub project funded by ERDF (EU Regional Development Funding) and the Council of Tampere Region in 2019-2021 and 2022-2023. We are a team of professionals governed by Tampere University. We have also been funded by FIMA, Business Tampere, and Business Finland. AI Hub aims at consulting local SMEs in the use and application of artificial intelligence in business development. The hub provides help and guidance in the ability to adopt the newest software and technology in the field of AI. We encourage companies to contact us when facing AI related challenges. Some of our particular focuses include intelligent machines, such as autonomous, driverless construction machines, robotics and ChatGPT.

We are the first industry-academia partnership to jointly educate researchers on heavy-duty mobile machinery. The first of its kind that will address the need for dramatic improvements in HDM machinery and fill the gap in related research and training. Eight early stage researchers will be equipped with a set of research skills including robotics, machine learning, energy systems, as well as transferable skills such as entrepreneurship and career management.

Safe Reinforcement Learning in Non-Stationary Environments With Fast Adaptation and Disturbance Prediction. This project aims to develop a framework to enable safe and efficient reinforcement learning for robot control in non-stationary environments, leveraging control theoretical tools for fast adaptation and perception-based disturbance prediction.

PEAMS is a Business Finland funded co-innovation project with research partners from Tampere University and University of Helsinki. Project includes 4 company projects and 6 company pilots. The project is coordinated by FIMA. PEAMS project will deals with some of the most important challenges in the software development of Intelligent Mobile Machines

Working machines form a fleet of machines in a worksite. The site can be, for example, a mine, a harbor, a crop field, or a forest. The worksite can be arranged hierarchically such that the whole entity is worksite, containing fleet and infrastructure, the fleet containing machines, the machines containing components, such as electric motors, batteries, and so on.

The application of artificial intelligence in Finnish industry is increasing significantly. DIMECC Oy's LIFEX program, which was launched two years ago, tripled in scope when industry started a new MIDAS project focusing on artificial intelligence. Among the participants are Glaston, Novatron, Nokia Technologies, Epec and Tampere University of Technology.