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Empowering Tomorrow’s Engineers: The MORE project’s final event presents innovations in heavy-duty mobile machinery

The MORE project, an innovative initiative funded by the European Union, celebrated the culmination of its European Industrial Doctorate (EID) research and training program at a successful final event. The event showcased the achievements of 8 early-stage researchers (ESRs) who presented key outcomes from their individual projects addressing challenges in the construction, logistics, and forestry sectors.

MORE – Educating Europe`s Future Engineers in Next Generation Heavy Duty Mobile Machinery: Artificial Intelligence driven Robotisation, Energy Efficiency and Process Optimisation – is the first industry-academia partnership to jointly educate researchers on heavy-duty mobile machinery. It addresses the need for dramatic improvements in heavy-duty mobile machinery (HDMM) and fill the gap in related research and training. Over the past four years, the MORE ESRs have been equipped with a set of research skills including robotics, machine learning, energy systems, as well as transferable skills such as entrepreneurship and career management.

Held in Helsinki, Finland from 24 – 26 October, the MORE project’s final event marked a significant milestone in enhancing productivity and efficiency across key industries. Around 40 participants joined the event including HDMM company representatives, PhD students and members from the MORE network. The consortium, comprised of respected heavy-duty mobile equipment companies including J. Deere, Liebherr, Bosch Rexroth, HIAB, and Volvo CE, collaborated with four specialised academic groups to nurture a new generation of engineers equipped with cutting-edge knowledge and skills.

In addition to keynote lectures and a site visit to Aalto Robot Learning Lab, the event highlighted the accomplishments of the ESRs, unveiling innovative solutions resulting from digitalisation and artificial intelligence. The recordings from the MORE ESR presentations are available online.

Professor Reza Ghabcheloo, coordinator of the MORE project, Tampere University, shared his satisfaction with the ESRs’ journeys, stating, “This has been a very successful industrial doctorate program, we have achieved our goals, industry is happy of the results and would like to build a similar project, doctoral students are happy and wanted by industry after MORE.”

As Europe anticipates a future shaped by technology and human creativity, the MORE project exemplifies the synergy between academia and industry. This collaboration fosters a generation of engineers ready to leave a lasting impact on heavy-duty mobile machinery and the industries it serves. The ESRs have demonstrated that innovation has no boundaries when fueled by dedication and cooperation.

The MORE consortium at the final event in Espoo, Helsinki Finland

Fourth and final innovations and MORE newsletter

September 2023

Perception and Navigation for Heavy-Duty Machines

Towards robust perception and navigation solutions for heavy-duty machines operating in all-weather conditions

Heavy-duty machines operate in highly complex, unstructured, and cluttered environments like forests, construction, and mines. Several challenges arise when working in these complex environments due to environmental conditions like low visibility during adverse weather for outdoor sites and low illumination areas like mines. These working conditions put a cognitive burden on the operators and make the operation prone to accidents for the operators and the humans working near the machines. This leads to the increasing demand for semi-autonomous or autonomous systems either to reduce the burden on operators or to have completely autonomous systems. These autonomous solutions could include object detection, mapping, and navigation in the environment in challenging conditions requiring perception sensors like cameras, lidars, and radars. In this newsletter, we take a closer look into the usage of perception for detection and navigation for heavy-duty mobile machines (HDMMs). The first article describes how lidar sensors can be used effectively in a forest environment, while the second article explains how radar sensors could be effective for navigation in any scenario.

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Third Future innovations and MORE newsletter published

June 2023

Automation and Control for Heavy-Duty Machines

Reshaping the future of operations with artificial intelligence and technological advances

Technology has taken a trampoline-leap in recent years, with the advent of machine learning algorithms, software, and hardware that have completely redefined the idea of “learning from data”. Outside the hype train related to large language models and simulated games, there is real potential to leveraging these machine learning tools to design intelligent control systems for the fleet of heavy-duty machines and robots. In this newsletter, we take a closer look into the usage of artificial intelligence for heavy-duty mobile machines (HDMMs). The first article describes how AI can be used for automating wheel loaders. The second article explains what can be leveraged from the machine learning world by engineers for more efficient and high-preforming machines in construction.

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MORE at Scandinavian International Conference on Fluid Power (SICFP) 2023

The MORE partners and early stage researchers have travelled to Tampere, Finland to participate at the Scandinavian International Conference on Fluid Power (SICFP) 2023. The event organised by our coordinator, Tampere University, will explore the latest advancements and foster collaborations in the field of fluid power.

MORE is happy to be able to participate at this highly engaging and innovative conference and also to use this platform to disseminate results to key experts, engineers and researchers at in the field. If you are at the SICFP 2023, do not miss out on hearing about our project either at the IHA Demo Night (1 June, 18:00–22:00) or at our early stage researchers presentations listed below:

31 May 2023

Tyrone J. Machado (ESR1), Bosch Rexroth AG, Germany, Industry Perspective of Stakeholder Relationships in the Technology Transition and Automation of Heavy-Duty Mobile Machinery in Session B2: Safety, business, and productivity (14:20-16:20)

Amirmasoud Molaei (ESR2), Karlsruhe Institute of Technology (KIT) / Novatron Oy, Germany/Finland, A Novel Framework for the Estimation of Excavator’s Actual Productivity in the Grading Operation Using Building Information Modeling (BIM) in Session B2: Safety, business, and productivity (14:20-16:20)

1 June 2023

Paolo Forte (ESR3), Örebro University/Novatron Oy, Sweden/Finland, From Blocks to Fine-Grained Material: on the Limitations of Discretizing Continuous Quantities for Task and Motion Planning in Construction-Sites in Session A3: Automation (10:30-12:10)

Daniel Eriksson (ESR6), Tampere University, Finland, Towards Multiple Material Loading for Wheel Loaders Using Transfer Learning in Session A3: Automation (10:30-12:10)

Abdolreza Taheri (ESR8), Tampere University / HIAB, Sweden, Towards Energy Efficient Control for Commercial Heavy-Duty Mobile Cranes: Modeling Hydraulic Pressures Using Machine Learning in Session A4: Control (13:00-14:40)

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Second Future innovations and MORE newsletter published

Autonomous heavy-duty mobile machines: Why and how can we use them in construction sites?

From manual to automatic material flow based on machine productivity in construction sites

In this newsletter, we want to discuss how fleets of (semi)autonomous Heavy-Duty Mobile Machines (HDMMs) could be used not only to complete a construction project, but to accomplish that in an optimal way. Optimization is essential to improve productivity and efficiency and reduce cost and project time. Nowadays, manual methods are employed to allocate tasks to construction machines based on the experience of worksite managers and manual observation of operations. However, these methods are costly, error prone, and depend on few experts that must always be available. Automating task planning and assignment based on fleet productivity can be a promising solution for solving the above challenges and achieving optimality. Firstly, Amirmasoud will describe how to estimate the productivity of a fleet of HDMMs during earth-moving tasks; secondly, Paolo will focus on optimizing the performance of the fleet of autonomous machines by solving task planning, task assignment, motion planning, and coordination problems jointly.

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First Future innovations and MORE newsletter published

Hot Topics for Heavy-Duty Mobile Machines

What’s going on and what can we expect?

In this newsletter, we want to have a closer look at the trends that define the current developments in the heavy-duty mobile machine (HDMM) sector. This way, you will get to know what is influencing as well as motivating our work in the MORE project. David will start by elaborating topical powertrain technology with a focus on construction machinery, and Tyrone will highlight some developments within automated and autonomous HDMMs.

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