Abstract
A laser scanner is a popular sensor widely used in industry and mobile robots applications that measures the distance to the sensor on a slice of the plan. This sensor can be used in mobile robots localization task. In this paper, a low cost laser scanner sensor is modelled so that it can be implemented in a simulation environment. The simulation reflects the laser model properties such as target colour dependences, noise, limits and time constraints. A correction of the laser scanner nonlinearities is proposed. The noise spectrum is also addressed.

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
Recognizing a place with a visual glance is the first capacity used by humans to understand where they are. Making this capacity available to robots will make it possible to increase the redundancy of the localization systems available in the robots, and improve semantic localization systems. However, to achieve this capacity it is necessary to build a robust visual signature that could be used by a classifier. This paper presents a new approach to extract a global descriptor from an image that can be used as the visual signature for indoor scenarios. This global descriptor was tested using videos acquired from three robots in three different indoor scenarios. This descriptor has shown good accuracy and computational performance when compared to other local and global descriptors.

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.