We presentCentury Maze,1 a simulated environment for cooperative navigation of groups numbering over 100 robots with primarily visual observations. The underlying task of large-scale object search is designed to push the scalability and efficiency of decentralized multi-robot systems relying on communication to overcome the limitations of separate units. To enable the training of robotic agents in large-scale visual embodied applications such asCentury Maze, we propose two reinforcement learning (RL) components that facilitate the emergence of effective communication:Differentiable Inter-Agent Belief Learning (DIABL), which provides a clear learning signal by optimizing the agents' beliefs about their goals and propagating gradients back over a differentiable communication channel to include the appropriate observers, andInformative Event Replay (InfER), which compensates for the scarcity of samples relevant toDIABLby maintaining a dedicated buffer for auxiliary learning. We demonstrate our combined method through an actor-critic neural network architecture encompassing a decentralized multi-agent system of variable size with individual goal-based belief modules. Results onCentury Mazeshow that our method is able to significantly improve performance through cooperation between over 100 agents against comparable baselines and maintains its effectiveness in realistic conditions.

In this paper an outline of the Erasmus+ program is given. Cooperation among organizations and institutions (Key Action 2 of Erasmus+ Programme) is described in a little more detail, because the TET project is part of this initiative. The motivation for the project is presented first as this is the key component when the needs analysis must be done as a part of the project proposal. This is followed by the description of the partnership and the planned project implementation.

The paper presents an overview and the main results of the Erasmus+ project titled Interactive Course for Control Theory – ICCT. The project was started by four European Universities when they identified by a survey that students find Control Theory more challenging to understand compared to other subjects. The project’s main goal was to develop a platform, which would offer examples from the field of Control Theory in an interactive way – ICCT. Frequently asked questions (FAQ) and test exam questions were added as well. To support the course, an accompanying textbook was prepared. At this point, the course and the accompanying textbook are available in English and the languages of the partner universities; since both of them are publicly available, we assume they will be offered in other languages in future. The benefits of implementing our interactive course are already visible in better survey results and improved grades in Control Theory-related subjects.

This paper presents the nanorobotic resistance spot welding (RSW) of ultra-thin film three-dimensional helical nanobelts(HNBs) for the assembly of nanoelectromechanical systems (NEMS) from as-fabricated building blocks. Three-dimensional HNBs with metal pads firstly placed onto as-fabricated micropipette electrode. using nanorobotic manipulation, then fixed with RSW. The spot-welded structures are then electro-mechanically characterized to show the ohmic conductivity and electromechanical stability. Experiments show that RSW can enable stable ohmic contacts with sufficient mechanical strength for constructing devices such as force sensors from HNBs.

This article describes a possible application of intelligent space as a platform for fire detection purposes. It enables fast and reliable fire detection, which is important for fire damage minimization. As Intelligent Space is primarily designed for other purposes, such as mobile robot guidance, its application for Are detection related purposes includes only the addition of new software. As almost no new hardware is needed it should be applied in all areas where Intelligent Space is installed.