Abstract
Solving the robot localization problem is one of the most necessary requirements for autonomous robots. Several methodologies can be used to determine its location as accurately as possible. What makes this difficult is the existence of uncertainty in the sensing of the robot. The uncertain information needs to be combined in an optimal way. This paper stresses a Kalman filter to combine information from the odometry and Ultra Wide Band Time of Flight distance modules, which lacks the orientation. The proposed system validated in a real developed platform performs the fusion task which outputs position and orientation of the robot. It is used to localize the robot and make a 3 DoF scanning of magnetic field in a room. Other examples can be pointed out with the same localization techniques in service and industrial autonomous robots. © Springer International Publishing AG 2018.

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
The localization systems are becoming more and more required in the actual flexible manufacturing systems based on mobile robots. There are several approaches to localize a mobile robot such as laser scanners reflective beacons, image mapping, lightning based systems, Ultra-wideband time-of-flight trilateration, odometry and fusion sensor data algorithms. During the development phase of a localization methodology, it is necessary to evaluate the proposed system: it is used a ground truth system. Ground truth systems are precise (usually based on reflective beacons) but expensive. This paper presents a low-cost ground truth system based on a standard low-cost laser scanner that, coupled with the presented algorithm, allows to localize the robot in the field and thus evaluate other localization systems. Results of the precision of the developed system are presented and validates the approach. Copyright

Abstract
The ionizing radiation is used in the nuclear medicine field during the execution of diagnosis exams. The administration of nuclear radio pharmaceutical components to the patient contaminates the environment. The main contribution of this work is to propose a path planning method for scanning the nuclear contaminated environment with a mobile robot optimizing the traveled distance. The Genetic Algorithm methodology is proposed and compared with other approaches and the final solution is validated in simulated and real environment in order to achieve a closer approximation to reality. © 2018, Springer International Publishing AG, part of Springer Nature.

Abstract
Develop cost-effective ground robots for crop monitoring in steep slope vineyards is a complex challenge. The terrain presents harsh conditions for mobile robots and most of the time there is no one available to give support to the robots. So, a fully autonomous steep-slope robot requires a robust automatic recharging system. This work proposes a multilevel system that monitors a vineyard robot autonomy, to plan off-line the trajectory to the nearest recharging point and dock the robot on that recharging point considering visual tags. The proposed system called VineRecharge was developed to be deployed into a cost-effective robot with low computational power. Besides, this paper benchmarks several visual tags and detectors and integrates the best one into the VineRecharge system. © Springer International Publishing AG 2018.

Abstract
One of the most important tasks for a mobile robot is to navigate in an environment. The path planning is required to design the trajectory that generates useful motions from the original to the desired position. There are several methodologies to perform the path planning. In this paper, a new method of approximate cells decomposition, called K-Framed Quadtrees is present, to which the algorithm A ? is applied to determine trajectories between two points. To validate the new approach, we made a comparative analysis between the present method, the grid decomposition, quadtree decomposition and framed quadtree decomposition. Results and implementation specifications of the four methods are presented. © 2018, Springer International Publishing AG.