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.

Abstract
The new paradigms of Industry 4.0 demand the collaboration between robot and humans. They could help and collaborate each other without any additional safety unlike other manipulators. The robot should have the ability of acquire the environment and plan (or re-plan) on-the-fly the movement avoiding the obstacles and people. This paper proposes a system that acquires the environment space, based on a kinect sensor, performs the path planning of a UR5 manipulator for pick and place tasks while avoiding the objects, based on the point cloud from kinect. Results allow to validate the proposed system. © Springer International Publishing AG 2018.

Abstract
The actual control quality standards require manufacturers to increase the inspection process. Instead of a sampling method, all items should be inspected and different equipment with different characteristics in the inspection cell need an adaptive system and the control quality cells should be enhanced. The presented work describes a self-adaptable robotized inspection cell for HMI consoles. which comprises the image acquisition system with controlled illumination and a force feedback sensor manipulated by a collaborative robot. The developed robotized cell is capable of detecting different HMI consoles and adapting the inspection routines of the manipulator robot according to the specific console. Moreover, the flexibility of the collaborative robot allows to adapt the camera positioning, lighting, and distance in a way that future HMI consoles can be inspected based on learning strategies.