Abstract
The COVID-19 virus outbreak led to the need of developing smart disinfection systems, not only to protect the people that usually frequent public spaces but also to protect those who have to subject themselves to the contaminated areas. In this paper it is developed a human detector smart sensor for autonomous disinfection mobile robot that use Ultra Violet C type light for the disinfection task and stops the disinfection system when a human is detected around the robot in all directions. UVC light is dangerous for humans and thus the need for a human detection system that will protect them by disabling the disinfection process, as soon as a person is detected. This system uses a Raspberry Pi Camera with a Single Shot Detector (SSD) Mobilenet neural network to identify and detect persons. It also has a FLIR 3.5 Thermal camera that measures temperatures that are used to detect humans when within a certain range of temperatures. The normal human skin temperature is the reference value for the range definition. The results show that the fusion of both sensors data improves the system performance, compared to when the sensors are used individually. One of the tests performed proves that the system is able to distinguish a person in a picture from a real person by fusing the thermal camera and the visible light camera data. The detection results validate the proposed system.

Abstract
Internet of Things, IoT, is a promising methodology that has been increasing over the last years. It can be used to allow the connection and exchange data with other devices and systems over the Internet. One of the IoT connection protocols is the LoRaWAN, which has several advantages but has a low bandwidth and limited data transfer. There is a necessity of optimising the data transfer between devices. Some sensors have a 10 or 12 bits resolution, while LoRaWAN owns 8 bits or multiples slots of transmission remaining unused bits. This paper addresses a communication optimisation for wireless sensors resorting to encoding and decoding procedures. This approach is applied and validated on the real scenario of a wildfire detection system.

Abstract
Nowadays, with the availability of 3D printers, the scanners for objects are becoming increasingly present since they allow to replicate objects by 3D printing, especially for small scale sizes. However, the majority of these technologies are expensive, due to the complexity of this task. Therefore, this work presents a prototype of a low-cost 3D scanning system for small objects using a point cloud to stereolithography approach where it was already validated in simulation in previous work. This concept has a restriction that the objects must have a uniform shape, i.e, without discontinuities. The architecture is composed of two stepper motors, due to their precision, a rotating plate to allow 360 degrees scans and another rotating structure that allows the infrared distance sensor to scan the object from bottom to top (90 degrees). The prototype was validated in the real scenario with good results.

Abstract
Automated guided vehicles (AGV) represent a key element in industries’ intralogistics and the use of AGV fleets bring multiple advantages. Nevertheless, coordinating a fleet of AGV is already a complex task but when exposed to delays in the trajectory and communication faults it can represent a threat, compromising the safety, productivity and efficiency of these systems. Concerning this matter, trajectory planning algorithms allied with supervisory systems have been studied and developed. This article aims to, based on work developed previously, implement and test a Multi AGV Supervisory System on real robots and analyse how the system responds to the dynamic of a real environment, analysing its intervention, what influences it and how the execution time is affected.

Abstract
The accumulation of dust particles on the solar panels decrease the total amount of solar energy received by the Photovoltaic panel (PV) and, it has also been proven that the increase of temperature reduces the overall efficiency. These effects have been studied by different researchers based on collected data comparison. As both of these parameters have a negative effect on the efficiency of the solar panel, it is essential to keep them clean and at low temperatures. The use of technologies, such as robots, is an effective way of carrying out repetitive tasks at low cost and in a short time. This work consists of developing a robot capable of cleaning and cooling the solar panels, based on images acquired through a camera positioned directly towards the panels, thus maintaining periodic cleaning in order to increase its efficiency. The preliminary results demonstrate the possibility of using this approach for the accomplishment of this task.

Abstract
In order to study the behavior and performance of a robot, building its simulation model is crucial. Realistic simulation tools using physics engines enable faster, more accurate and realistic testing conditions, without depending on the real vehicle. By combining legged and wheeled locomotion, hybrid vehicles are specially useful for operating in different types of terrains, both indoors and outdoors. They present increased mobility, versatility and adaptability, as well as easier maneuverability, when compared to vehicles using only one of the mechanisms. This paper presents the realistic simulation through the SimTwo simulator software of a hybrid legged-wheeled robot. It has four 3-DOF (degrees of freedom) legs combining rigid and non-rigid joints and has been fully designed, tested and validated in the simulated environment with incorporated dynamics.