Abstract
Long-term operation of robots creates new challenges to Simultaneous Localization and Mapping (SLAM) algorithms. Long-term SLAM algorithms should adapt to recent changes while preserving older states, when dealing with appearance variations (lighting, daytime, weather, or seasonal) or environment reconfiguration. When also operating robots for long periods and trajectory lengths, the map should readjust to environment changes but not grow indefinitely. The map size should depend only on updating the map with new information of interest, not on the operation time or trajectory length. Although several studies in the literature review SLAM algorithms, none of the studies focus on the challenges associated to lifelong SLAM. Thus, this paper presents a systematic literature review on long-term localization and mapping following the Preferred Reporting Items for Systematic reviews and Meta-Analysis guidelines. The review analyzes 142 works covering appearance invariance, modeling the environment dynamics, map size management, multisession, and computational topics such as parallel computing and timing efficiency. The analysis also focus on the experimental data and evaluation metrics commonly used to assess long-term autonomy. Moreover, an overview over the bibliographic data of the 142 records provides analysis in terms of keywords and authorship co-occurrence to identify the terms more used in long-term SLAM and research networks between authors, respectively. Future studies can update this paper thanks to the systematic methodology presented in the review and the public GitHub repository with all the documentation and scripts used during the review process.

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
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
Data acquisition is a critical task for localisation and perception of mobile robots. It is necessary to compute the relative pose between onboard sensors to process the data in a common frame. Thus, extrinsic calibration computes the sensor’s relative pose improving data consistency between them. This paper performs a literature review on extrinsic sensor calibration methods prioritising the most recent ones. The sensors types considered were laser scanners, cameras and IMUs. It was found methods for robot–laser, laser–laser, laser–camera, robot–camera, camera–camera, camera–IMU, IMU–IMU and laser–IMU calibration. The analysed methods allow the full calibration of a sensory system composed of lasers, cameras and IMUs. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021.

Abstract
The pose control (position and orientation) of a robot is important to control how and when the robot gets to the desired pose at the desired time in order to perform some task. Controlling omnidirectional robots is of great interest due to their complete maneuverability. So, we use Proportional-Integrative (PI), Proportional-Derivative (PD), and Feed-Forward (FF) controllers to control the pose of an omnidirectional robot in space and in time. The proposed controller approximates the future trajectory (a subset of points) on parametric polynomials for computing the derivatives needed in the FF. In the simulations performed, it was analyzed the size of the future trajectory horizon for the controller depending on the robot's velocity, and the proposed controller was compared to PD-only and a generic GoToXY controller. The results demonstrated that the proposed controller achieves better results than the other two both in space and in time.