Abstract
Particle filters are sequential Monte Carlo estimation methods with applications in the field of mobile robotics for performing tasks such as tracking, simultaneous localization and mapping (SLAM) and navigation, by dealing with the uncertainties and/or noise generated by the sensors as well as with the intrinsic uncertainties of the environment. This work presents a field programmable gate arrays (FPGA) implementation of a particle filter applied to SLAM problem based on a low cost Neato XV-11 laser scanner sensor. Post processing is performed on data provided by a realistic simulation of a differential robot, equipped with a hacked Neato XV-11 laser scanner, that navigates in the Robot@Factory competition maze. The robot was simulated using SimTwo, which is a realistic simulation software that can support several types of robots. The simulator provides the robot ground truth, odometry and the laser scanner data. The results achieved from this study confirmed the possible use such low cost laser scanner for different robotics applications.

Abstract
Purpose - This paper aims to address a mobile robot localization system that avoids using a dedicated laser scanner, making it possible to reduce implementation costs and the robot's size. The system has enough precision and robustness to meet the requirements of industrial environments. Design/methodology/approach - Using an algorithm for artificial beacon detection combined with a Kalman Filter and an outlier rejection method, it was possible to enhance the precision and robustness of the overall localization system. Findings - Usually, industrial automatic guide vehicles feature two kinds of lasers: one for navigation placed on top of the robot and another for obstacle detection (security lasers). Recently, security lasers extended their output data with obstacle distance (contours) and reflectivity. These new features made it possible to develop a novel localization system based on a security laser. Research limitations/implications - Once the proposed methodology is completely validated, in the future, a scheme for global localization and failure detection should be addressed. Practical implications - This paper presents a comparison between the presented approach and a commercial localization system for industry. The proposed algorithms were tested in an industrial application under realistic working conditions. Social implications - The presented methodology represents a gain in the effective cost of the mobile robot platform, as it discards the need for a dedicated laser for localization purposes. Originality/value - This paper presents a novel approach that benefits from the presence of a security laser on mobile robots (mandatory sensor when considering industrial applications), using it simultaneously with other sensors, not only to guarantee safety conditions during operation but also to locate the robot in the environment. This paper is also valuable because of the comparison made with a commercialized system, as well as the tests conducted in real industrial environments, which prove that the approach presented is suitable for working under these demanding conditions.

Abstract
This paper addresses the development of a new localization system based on a security laser presented on most AGVs for safety reasons. An enhanced artificial beacons detection algorithm is applied with a combination of a Kalman filter and an outliers rejection method in order to increase the robustness and precision of the system. This new robust approach allows to implement such system in current AGVs. Real results in industrial environment validate the proposed methodology.

Abstract
Self-localization of a robot in an indoor plant is one of the most important requirement in mobile robotics. This paper addresses the application and improvement of a well known localization algorithm used in Robocup Midsize league competition in real service and industrial robots. This new robust approach is based on modeling the quality of several measures and minimizing the maching error. The presented innovative work applies the robotic football knowledge to other fields with high accuracy. Real and simulated results allow to validate the proposed methodology.

Abstract
Vision-based mobile robots have severe limitations related to the computational capabilities that are required for processing their algorithms. The vision algorithms processed onboard and without resorting to specialized computing devices do not achieve the real-time constraints that are imposed by that kind of systems. This paper describes a scheme for streaming image sequences in order to be used by techniques of artificial vision. A mobile robot with this architecture can stream image sequences over the network infrastructure for a device with higher computing power. Therefore, the robot assures the real-time performance with a reduced consumption of energy which increases its autonomy. The experiments conducted without using specialized computers proved that the proposed architecture can stream sequences of images with a resolution of 640x480 at 25 frames per second.

Abstract
This paper describes a laboratory control theory experiment supported by the use of a DCMotor Educational Kit. The impact, as a teaching aid, of the proposed laboratory control experiment is evaluated, having in mind the student’s feedback. The DC motor that is used in the developed educational Kit is the EMG30, being a low cost 12V motor equipped with encoders and a 30:1 reduction gearbox. The experiment is based on real hardware and on simulation, using the SimTwo realistic simulation software. In order to implement the realistic simulation the EMG30model was obtained. Students’ feedback was acquired using a questionnaire and the results confirmed the importance given to these practical experiments. © Springer International Publishing Switzerland 2017.