Intuitive and self-learning robots
The Department of Industrial Engineering coordinates an 8 million research project in the field of collaborative robotics. The European funding will help build devices that are capable of changing their behaviour without human intervention
Industries are increasingly relying on robotics to manage industrial control systems and production processes. Robots replace human work, increase the speed of performance, are effective in precision mechanical work. However, increasingly advanced equipment must be continuously updated with new operational tasks, and it has a considerable environmental impact when it becomes obsolete and must be disposed of.
Thanks to European funding, a working group of the University of Trento will spend the next four years designing a robotic device capable of modifying its behaviour and adapting to different situations without the intervention of humans. The plan of the University of Trento, developed by Matteo Saveriano, a researcher of the Department of Industrial Engineering and European coordinator of the Inverse project, aims to push the limits: its goal is to create robots with the necessary cognitive abilities to understand the surrounding environment, including human intentions and needs, decide what actions to take, adapt them, and make the necessary adjustments. Robots that are interactive but also intuitive.
«We started from a very specific machine learning problem, that is the generation of safe and sensible behaviour when devices are outside the world of training data, that is data acquired through artificial intelligence algorithms», explains Matteo Saveriano. In particular, the project addresses the problem for a robot to change a previously learned task in complete autonomy, without the intervention of an operator.
The project will have application settings in two sectors: the automotive industry and the heavy industry. In the first case, the system will be tested to assemble, disassemble and recycle the batteries of electric vehicles. The robotic device will be instructed to install a battery. But the ultimate goal of the project is that the robot uses this knowledge to explore the needs of the setting in which it operates and take apart the battery.
In the heavy mechanical industry, the system will instead be used to facilitate an intelligent interaction between an operator, the robotic device and an automated overhead crane. In this case, the goal is to automate the cranes, which are used for lifting and moving large and heavy metal loads from one point to another at a company facility. Currently, there is an operator performing this work who also operates the overhead crane and often works in an uncomfortable and dangerous position, where accidents are likely to occur. The robotic device will therefore replace the human in risky or unpleasant tasks. Operators will continue to supervise the work along the entire production process. «Our idea is to let operators perform less repetitive and heavy tasks so that they can use all the intellectual abilities of human intelligence such as imagination and the ability to solve problems, that machines cannot do. We would like let robots handle the materials and put people in a safer position. In this way, humans would supervise the work of machines and make sure it is as precise as possible» adds Saveriano.
The project is in line with the policies of the European Union on the circular and green economy. One of the great problems of the automotive industry is the recycling of battery components. Today batteries are manufactured by different companies, with different assembly techniques. The sorting, disposal and reuse of these materials is a very complex task because no two batteries are the same. What Inverse aims to achieve is to automate this process by developing highly innovative solutions and flexible learning techniques that adapt quickly to the components of the battery.
In addition to this, the robotic devices will be able to measure the energy efficiency of a product, the amount of greenhouse gases they emit, the materials they use and their recycling rate, to make a positive contribution to the disposal of industrial waste.
But the project also has other sustainability goals. The researchers want that the device that has been trained for the purpose of assembling can be used, with small changes, for disassembling, to scientifically demonstrate that this is more convenient than training a device from scratch.
The Inverse project
Inverse is the result of the collaboration among the Idra interdepartmental laboratories of robotics of the University of Trento, which also include the Department of Information Engineering and Computer Science.
Of the ten partners of the project, six are universities and research institutes: the Create consortium of Federico II University of Naples, the University of Vienna, the Technical Research Centre of Finland, the German Space Agency (Dlr), the Universities of Mondragon (Spain) and Bogazici (Turkey). The other four partners are from the industrial sector: Centro Ricerche Fiat, KroneCrane AG, Steinbeis Europa Zentrum, MTU Civitta Foundation.
This is a Research and Innovation Action – RIA project that has obtained eight million euros funding from the European Union. The project will start in January. The goal of researchers is to create, by 2027, the first prototype of a robot tested in a laboratory environment that simulates an industrial setting.