Abstract
In this paper it is described a new Servo Motor Optimised for Educational Robotic Applications (SMORA), which comprises several sensors and higher level addressing/communication capabilities. Even though servos have excellent qualities when used in the field of robotics, several properties can still be enhanced. These devices are known to have nonlinear properties and dynamic factors such as dead-zones, backlash and friction that might hinder their precision and accuracy. They usually do not provide position, velocity or current feedback to the device controlling them. Factors such as change in the load attached to the system increase the complexity of the analysis even further. Controlling these servos using a PWM signal might also become complicated if the number of servo motors to control increases. The new proposed servo consists of custom hardware and firmware that includes a microcontroller and a series of sensors, allowing for the motor current, temperature and voltage to be measured in real-time as well as precise position feedback thanks to the integrated hall-effect magnetic position encoder. It also incorporates an accelerometer and a gyroscope to measure the servo body relative position and rotation.

Abstract
Aerial Robots has become very popular in robotics groups. This ongoing interest is driven by a significant number of potential end-user applications where it is necessary to reduce human intervention. The validation of control/cooperation algorithms not always is an easy task and requires a large number of humans to keep tests safety. Is present in this paper the simulation of a quadrotor model in SimTwo simulation environment and evaluated the flight dynamic of the robot. To do that was developed a control layer responsible to the hovering maneuver and “go to” position function. The results prove that the objectives were achieved successfully and the simulation was validated. The navigation simulation is left as future work.

Abstract
NaSSIE - Navigation and Sensoring Skills in Engineering is a platform developed with the intent of facilitating the acquisition of some skills by Engineering Students, which is a core part of the process of controlling a mobile robot. In this paper, the chosen hardware and consequent physical construction of the prototype as well as vehicle’s associated software will be presented. As a use case, this platform was tested during the Robotic Day 2017 in Czech Republic. Preliminary results will also be presented of this year’s preparation for the Micromouse competition. © 2019, Springer Nature Switzerland AG.

Abstract
The self-localization of mobile robots in the environment is one of the most fundamental problems in the robotics navigation field. It is a complex and challenging problem due to the high requirements of autonomous mobile vehicles, particularly with regard to the algorithms accuracy, robustness and computational efficiency. In this paper, we present a comparison of three of the most used map-matching algorithms applied in localization based on natural landmarks: our implementation of the Perfect Match (PM) and the Point Cloud Library (PCL) implementation of the Iterative Closest Point (ICP) and the Normal Distribution Transform (NDT). For the purpose of this comparison we have considered a set of representative metrics, such as pose estimation accuracy, computational efficiency, convergence speed, maximum admissible initialization error and robustness to the presence of outliers in the robots sensors data. The test results were retrieved using our ROS natural landmark public dataset, containing several tests with simulated and real sensor data. The performance and robustness of the Perfect Match is highlighted throughout this article and is of paramount importance for real-time embedded systems with limited computing power that require accurate pose estimation and fast reaction times for high speed navigation. Moreover, we added to PCL a new algorithm for performing correspondence estimation using lookup tables that was inspired by the PM approach to solve this problem. This new method for computing the closest map point to a given sensor reading proved to be 40 to 60 times faster than the existing k-d tree approach in PCL and allowed the Iterative Closest Point algorithm to perform point cloud registration 5 to 9 times faster.

Abstract
Robotics competitions are increasing in complexity and number challenging the researchers, roboticists and enthusiastic to address the robot applications. One of the well-known competition is the micromouse where the fastest mobile robot to solve a maze is the winner. There are several topics addressed in this competition such as robot prototyping, control, electronics, path planning, optimization, among others. A simulation can be used to speed-up the development and testing algorithms but faces the gap between the reality in the dynamics behaviour. In this paper, an open source realistic simulator tool is presented where the dynamics of the robot, the slippage of the wheels, the friction and the 3D visualization can be found. The complete simulator with the robot model and an example is available that allow the users to test, implement and change all the environment. The presented results validate the proposed simulator. © 2019, Springer Nature Switzerland AG.

Abstract
In this paper it is presented a line follower educational mobile robot performance robustness increase. The Robotic Day line Follower Competition was used as a Benchmark to test the proposed approach. The applied robot is based on an Arduino, which is applied in the low level control, while the high level control loop is carried out by an RPI running an object pascal application. The described robot was prototyped in order to have a competitive participation in the Robotic Day Line Follower 2017 competition, and improved for performance robustness increase in order to participate in the 2018 competition. It was prototyped with an RPI, taking advantage of its capabilities, allowing the use of higher performance sensors, when compared with the most common standard approaches based on a single 8 bit RISC micro-controller, having as disadvantage the inevitable robot size increase, which compromises in certain situations the robot maneuverability and increases the power consumption. The robot is equipped with DC Motors, the chosen line follower sensor is the picamera and for the obstacle detection, a time of flight sensor was applied.