Abstract
Motion control is an important task in several areas, such as robotics where the angular position and speed should be acquired, usually with encoders. For slow angular speeds, an error is introduced spoiling the measurement. In this paper there will be proposed two new methodologies, that when combined allow to increase the precision whereas reducing the error, even on transient velocities. The two methodologies Variable Acquisition Window and a Quadrature Phase Compensation are addressed and combined simultaneously. A real implementation of the proposed algorithms is performed on a real hardware, with a DC motor and a low resolution encoder based on hall effect. The results validate the proposed approach since the errors are reduced compared with the standard Quadrature Encoder Reading.

Abstract
Legged-wheeled locomotion systems are a particular case of robot types that can be characterized by an increase in the degrees of freedom. To increase safety and robustness in the performance of industrial robots, while reducing the risk of damage to the robot joints and injure to human operators, the use of non-rigid joints is growing in the literature and in the industry. Realistic simulators are tools capable of detecting rigid bodies interactions through physics engines. This paper presents the simulation model of a hybrid legged-wheeled robot, built in the SimTwo simulator. The proposed algorithms for path following control are detailed, along with the tests performed to them. These showed that the errors in linear paths are at most 1 cm. For circular paths, the maximum error is 3 cm.

Abstract
The proposed work was developed as part of the SmartHealth project, which aims to advance upper body rehabilitation by granting a robotic alternative to reduce the limitations of physical therapy while conferring more intensive and personalized therapy sessions for patients. The use of robots permits therapists to be relieved of laborious and repetitive tasks while supplying feedback for patients and physiotherapists through automatic recordings. The proposed strategy is to develop new python-based software that controls the robot, collects the patient's forces and muscle activity in real-time, and stores them for future analysis while providing visual feedback, thus allowing session optimization. These features permit the physiotherapist to objectively perceive the patient's performance during exercise. This solution is implemented in robots already commercialized in the industrial field. These kinds of robots are generally mass-produced in production lines at a relatively low cost and with great flexibility.

Abstract
Robotics competitions encourage the development of solutions to new challenges that emerge in sync with the rise of Industry 4.0. In this context, robotic simulators are employed to facilitate the development of these solutions by disseminating knowledge in robotics, Education 4.0, and STEM. The RobotAtFactory 4.0 competition arises to promote improvements in industrial challenges related to autonomous robots. The official organization provides the simulation scene of the competition through the open-source SimTwo simulator. This paper aims to integrate the SiwTwo simulator with the Robot Operating System (ROS) middleware by developing a framework. This integration facilitates the design of robotic systems since ROS has a vast repository of packages that address common problems in robotics. Thus, competitors can use this framework to develop their solutions through ROS, allowing the simulated and real systems to be integrated.

Abstract
In view of the actual climate change scenario felt across the globe, resource management is crucial, especially with regard to water. In this sense, continuous monitoring of plant water status is essential to optimise not only crop management but also water resources. Currently, monitoring of vine water status is done through expensive and time-consuming methods that do not allow continuous monitoring, which is especially inconvenient in places with difficult access. The aim of the developed work was to install three groups of sensors (Environmental, Plant and Soil) in a vineyard and connect them through LoRaWAN protocol for data transmission. The results demonstrate that the implemented system is capable of continuous data communication without data loss. The reduced cost and superior range of LoRaWAN compared to WiFi or Bluetooth is especially important for applications in remote areas where cellular networks have little coverage. Altogether, this methodology provides a remote, continuous and more effective method to monitor plant water status and is capable of supporting producers in more efficient management of their farms and water resources.

Abstract
Counterfeit medicine is still a crucial problem for healthcare systems, having a huge impact in worldwide health and economy. Medicine packages can be traced from the moment of their production until they are delivered to the costumers through the use of Data Matrix codes, unique identifiers that can validate their authenticity. Currently, many practitioners at hospital pharmacies have to manually scan such codes one by one, a very repetitive and burdensome task. In this paper, a system which can simultaneously scan multiple Data Matrix codes and autonomously introduce them into an authentication database is proposed for the Hospital Pharmacy of the Centro Hospitalar de Vila Nova de Gaia/Espinho, E.P.E. Relevant features are its low cost and its seamless integration in their infrastructure. The results of the experiments were encouraging, and with upgrades such as real-time feedback of the code's validation and increased robustness of the hardware system, it is expected that the system can be used as a real support to the pharmacists.