Abstract
The industry tends to increasingly automate as many processes as possible, and to make this possible, they often resort to the use of robotic arms. This paper presents the development of a proposal for a modular joint for robotic arms that allows: to obtain the best possible torque/weight ratio; to be controlled in speed and/or position; to communicate with other joints and external microcontrollers; to keep the cost as low as possible; and to be easily reconfigurable. The proposed prototype was validated with real results.

Abstract
Nowadays, a laboratory operator in the areas of chemistry, biology or medicine spends considerable time performing micropipetting procedures, a common, monotonous and repetitive task which compromises the ergonomics of individuals, namely related to wrist musculoskeletal disorders. In this work, the design of a kinesthetic teaching approach for automating the micropipetting technique is presented, allowing to redirect the operator to other non-repetitive tasks, aiming to reduce the exposure to ergonomic risks. The proposed robotic solution has an innovative gripping system capable of supporting, actuating and regulating the volume of a manual micropipette. The system is able to configure the position of diverse laboratory materials, such as lab containers and plates, on the workbench through a collaborative robotic arm, providing flexibility to adapt to different procedures. A projected human-machine interface, which combines the display of information on the workbench with an infrared based interaction device was developed, providing a more intuitive interaction between the operator and the system during the configuration and operation phases. In contrast to the majority of the existing liquid handling systems, the proposed system allows the operator to place the materials freely on the workbench and the usage of different materials' variants, facilitating the implementation of the system in any laboratory. The attained performance and ease of use of the system were very encouraging since all the defined tasks in the conducted experiments were successfully performed by users with minimum training, highlighting its potential inclusion in the laboratory routine panorama.

Abstract
This paper presents a systematic mapping literature review about the mobile robotics competitions that took place over the last few decades in order to obtain an overview of the main objectives, target public, challenges, technologies used and final application area to show how these competitions have been contributing to education. In the review we found 673 papers from 5 different databases and at the end of the process, 75 papers were classified to extract all the relevant information using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method. More than 50 mobile robotics competitions were found and it was possible to analyze most of the competitions in detail in order to answer the research questions, finding the main goals, target public, challenges, technologies and application area, mainly in education.

Abstract
Odometry calibration adjusts the kinematic parameters or directly the robot's model to improve the wheeled odometry accuracy. The existent literature considers in the calibration procedure only one steering geometry (differential drive, Ackerman/tricycle, or omnidirectional). Our method, the OptiOdom calibration algorithm, generalizes the odometry calibration problem. It is developed an optimization-based approach that uses the improved Resilient Propagation without weight-backtracking (iRprop-) for estimating the kinematic parameters using only the position data of the robot. Even though a calibration path is suggested to be used in the calibration procedure, the OptiOdom method is not path-specific. In the experiments performed, the OptiOdom was tested using four different robots on a square, arbitrary, and suggested calibration paths. The OptiTrack motion capture system was used as a ground-truth. Overall, the use of OptiOdom led to improvements in the odometry accuracy (in terms of maximum distance and absolute orientation errors over the path) over the existent literature while being a generalized approach to the odometry calibration problem. The OptiOdom and the methods from the literature implemented in the article are available in GitHub as an open-source repository.

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.