Abstract
Task Scheduling assumes an integral topic in the efficiency of multiple mobile robots systems and is a key part in most modern manufacturing systems. Advances in the field of combinatorial optimisation have allowed the implementation of algorithms capable of solving the different variants of the vehicle routing problem in relation to different objectives. However few of this approaches are capable of taking into account the nuances associated with the coordinated path planning in multi-AGV systems. This paper presents a new study about the implementation of the Simulated Annealing algorithm to minimise the time and distance cost of executing a tasks set while taking into account possible pathing conflicts that may occur during the execution of the referred tasks. This implementation uses an estimation of the planned paths for the robots, provided by the Time Enhanced A* (TEA*) to determine where possible pathing conflicts occur and uses the Simulated Annealing algorithm to optimise the attribution of tasks to each robot, in order to minimise the pathing conflicts. Results are presented that validate the efficiency of this algorithm and compare it to an approach that does not take into account the estimation of the robots paths.

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
This paper describes the several steps to build an elaborate flight simulator cockpit, where the hardware is designed based on Mechatronic principles and the proposed software was developed using agile methodologies to create a Cyber-Physical System (CPS). Furthermore, this research attempts to simulate the real environment from an aircraft as close as possible with a real scale developed cockpit. Based on this, the presented paper contributions include: (1) The implementation of a complex dynamic system such as a CPS, where the Mechatronic system is part of it; (2) The deployment of a scale model of an Airbus A32x aircraft (one of the most used), integrating into a mathematical model adapted to the operation of an aircraft flight simulation system, regarding the physical forces involved. This project is also used to captivate the students' motivation to the areas of technology such as electronics and programming and permits its development as a student project and thesis. Results allow validating the proposed cockpit.

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.

Abstract
Robotics competitions are environments that foster teamwork, AI, and technology development by encouraging students, researchers, and academics to test their solutions against each other. These competitions often challenge the competitors' prototypes with tasks specifically designed to benchmark them with the current optimal solutions. During the prototype stages of a robot, the development costs and time spent are often higher than other stages, as changes in the prototype are frequent. Simulation is often used to reduce these variables as it allows flexibility in all development stages before transitioning to the real scenario. However, a digital twin can be used to increase even further flexibility and effectiveness. Digital twins are virtual representations of real assets, providing replication and prediction of real scenario events, and real-time monitoring of the real object. Thus, this paper presents the development of a digital twin of an automatic guided vehicle (AGV) to the Robot@Factory Lite competition and the tests performed to validate the approach.