Abstract
The flexibility and versatility associated with autonomous mobile robots (AMR) have facilitated their integration into different types of industries and tasks. However, as the main objective of their implementation on the factory floor is to optimize processes and, consequently, the time associated with them, it is necessary to take into account the environment and congestion to which they are subjected. Localization, on the shop floor and in real time, is an important requirement to optimize the AMRs' trajectory management, thus avoiding livelocks and deadlocks during their movements in partnership with manual forklift operators and logistic trains. Threeof the most commonly used localization techniques in indoor environments (time of flight, angle of arrival, and time difference of arrival), as well as two of the most commonly used indoor localization methods in the industry (ultra-wideband, and ultrasound), are presented and compared in this paper. Furthermore, it identifies and compares three industrial indoor localization solutions: Qorvo, Eliko Kio, and Marvelmind, implemented in an industrial mobile platform, which is the main contribution of this paper. These solutions can be applied to both AMRs and other mobile platforms, such as forklifts and logistic trains. In terms of results, the Marvelmind system, which uses an ultrasound method, was the best solution.

Abstract

Abstract
Low-cost, small-sized portable laboratories, or take-home laboratories, have been increasing in popularity worldwide. One example of such a successful Arduino-based kit is the Temperature Control Laboratory (TCLab), originally proposed by [1]. This kit has been used in Portugal for control engineering education since 2018. This paper proposes a TCLab demo session, reflecting the use of this kit in Portugal across different educational contexts. © 2023 IEEE.

Abstract
The recent release of ChatGPT-3 by OpenAI may have been a major disruptive mark in terms of Artificial Intelligence based tools. The testing and rapid user adoption rate of ChatGPT-3 was massive with a worldwide impact. Despite its recent public release ChatGPT-3 is already eliciting a mix of positive reactions revealing outstanding positive aspects as well as some negative ones. A short evaluation of ChatGPT-3 is presented, using the context of genetic algorithms, a topic lectured in introductory artificial intelligence courses. Examples outlining potential advantages of adopting ChatGPT and disadvantages which raise ethical issues and may limit its use are presented. © 2023 IEEE.

Abstract
Mobile robot platforms capable of operating safely and accurately in dynamic environments can have a multitude of applications, ranging from simple delivery tasks to advanced assembly operations. These abilities rely heavily on a robust navigation stack, which requires stable and accurate pose estimations within the environment. The wide range of AMR's applications and the characteristics of multiple industrial environments (indoor and outdoor) have led to the development of a flexible and robust robot software architecture that allows the fusion of different data sensors in real time. In this way, and in terms of localization, AMRs have greater precision when it comes to uncontrolled and unstructured environments. These complex environments feature a variety of dynamic and unpredictable elements, such as variable layouts, limited visibility, unstructured spaces, and uncertain terrain. This paper presents a multi-localization system for industrial mobile robots in complex and dynamic industrial scenarios, based on different localization technologies and methods that can interact together and simultaneously.

Abstract
Since creating universally capable robots is challenging for a single manufacturer, a diverse fleet of robots from various manufacturers is utilized. However, these heterogeneous fleets encounter communication and interoperability issues. As a result, there is a growing need for a standardized interface that is capable of communicating, controlling and managing a diverse fleet without these interoperability issues. This paper presents a translation software module capable of controlling an autonomous mobile robot and communicating with a ROS-based robot fleet manager using the VDA5050 Standard and exchanging information via the MQTT communication protocol, aiming at flexibility and control across different robot brands. The effectiveness of the software in controlling a mobile robot via the VDA5050 standard was demonstrated by the results. It accurately analysed data from the Robot Fleet Manager, converted it into VDA 5050 JSON messages and skilfully translated it back into ROS messages. The robot's behavior remained consistent before and after the VDA5050 implementation.