Abstract
In recent years, there has been great interest from researchers in legged robots. These robots have unique characteristics and are suitable for complex working environments with uneven terrains and unexpected obstacles. They can work on almost any type of terrain, overcome obstacles like stairs much more efficiently than wheeled or tracked robots, and cause a lower impact on the ground when compared with other locomotion systems. To expand the application of robotics to new complex areas, it is essential to accurately locate the robot and plan safe trajectories regardless of the environment, terrain, or weather conditions. Using a legged locomotion system raises some concerns regarding the 3D localization, mapping, and trajectory planning algorithms. This paper reviews those problems and describes the current approaches to localize a robot, map an environment and plan safe trajectories for quadruped robots.

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
Teleoperation of autonomous mobile robots (AMR) is relevant in logistics operations to automate repetitive tasks that often result in injuries to the operator. This paper presents an overview of the systems involved in the current teleoperation scheme where these AMRs are present as well as some works and advances that have been done in the high-level teleoperation field.

Abstract
The technological market is increasingly evolving as evidenced by the innovative and streamlined manufacturing processes. Printed Circuit Boards (PCB) are widely employed in the electronics fabrication industry, resorting to the Gerber open standard format to transfer the manufacturing data. The Gerber format describes not only metadata related to the manufacturing process but also the PCB image. To be able to map the electronic circuit pattern to be printed, a parser to convert Gerber files into a bitmap image is required. The current literature as well as available Gerber viewers and libraries showed limitations mainly in the Gerber format support, focusing only on a subset of commands. In this work, the development of a recursive descent approach for parsing Gerber files is described, outlining its interpretation and the renderization of 2D bitmap images. All the defined commands in the specification based on Gerber X2 generation were successfully rendered, unlike the tested commercial parsers used in the experiments. Moreover, the obtained results were comparable to those parsers regarding the commands they can execute as well as the ground-truth, emphasizing the accuracy of the proposed approach. Its top-down and recursive architecture allows easy integration with other software regardless of the platform, highlighting its potential inclusion and integration in the production of electronic circuits.

Abstract
In the manufacturing domain, the digital twin has become an emerging concept for decision-making through the integration of what-if simulation capabilities. In such systems, the processing of the entire space of alternative solutions is very time-consuming; recommendation systems are used to solve this; however, these suffer from several problems, namely data sparsity and cold-start. The application of trust-based models can mitigate these problems, particularly the cold-start problems, by providing valuable background for the recommendation system. This paper presents the implementation and experimental validation of a trust-based model for improving the digital twin based what-if simulation recommendation system, addressing the cold-start problems. The proposed trust model was applied in an assembly line case study to recommend the best configurations for the optimal number of AGVs (Autonomous Guided Vehicles). The results show that applying the trust-based model with similarity metrics improved the mitigation of the cold-start problem. © 2022 IEEE.