Abstract
The sensors that acquire 3D data play an important role in many applications. In addition, they have been used in the robotic field for several purposes, for instance, enhancing the navigation of mobile robots, object detection, scene reconstruction, 3D inspection of parts and others. Moreover, a significant amount of devices with distinct cost, accuracy and features have been released in the recent years which increases the difficulty of comparing each sensor in a proper manner or choosing the most suitable device for a specific task and operation field. This paper compares the Kinect v1, Kinect v2, Structure Sensor and Mesa Imaging SR4000. The noise of each sensor is characterized for different distances and considering objects with different colors. Therefore, this paper proposes a simple but quantitative benchmark for evaluating 3D devices that characterizes the most relevant features for the robotic field and in accordance with different type of operations.

Abstract
Human being has an extraordinary capability for motion perception due to its remarkable visual sensing system that makes it possible to perceive, distinguish and characterize the different moving elements of the environment. Thus, it extracts information through sensory experience and conducts reliable judgments based on intrinsic motion features, namely, location, direction, trajectory, magnitude, colors, boundary and shape. Unfortunately, the same cannot be said for mobile robots. The critical nature of visual perception for these kinds of systems turns motion detection and analysis as one of the most relevant areas discussed on the literature, existing several models and methods to perform motion analysis in a variety of environments. This paper discusses motion analysis for mobile robots. A brief description about the complexity of motion perception based on moving observations and for surveillance applications is presented. In addition, the most often encountered approaches and future orientations are also discussed.

Abstract
The Robot@Factory competition was recently included in Robotica, the main Portuguese Robotics Competition. This robot competition takes place in an emulated factory plant, where automatic guided vehicles (AGVs) must cooperate to perform tasks. To accomplish their goals, the AGVs must deal with localization, navigation, scheduling, and cooperation problems that must be solved autonomously. This robot competition can play an important role in education due to its inherent multidisciplinary approach, which can motivate students to bridge different technological areas. It can also play an important role in research and development, because it is expected that its outcomes will later be transferred to real-world problems in manufacturing or service robots. By presenting a scaled-down factory shop floor, this competition creates a benchmark that can be used to compare different approaches to the challenges that arise in this kind of environment. The ability to alter the environment, in some restricted areas, can usually promote the test and evaluation of different localization mechanisms, which is not possible in other competitions. This paper presents one of the possible approaches to build a robot capable of entering this competition. It can be used as a reference to current and new teams.

Abstract
Usually the Industrial Automatic Guide Vehicles (AGVs) have two kind of lasers. One for navigation on the top and others for obstacle detection (security lasers). Recently, security lasers extended its output data with obstacle distance (contours) and reflectivity, that allows the development of a novel localization system based on a security laser. This paper addresses a localization system that avoids a dedicated laser scanner reducing the implementations cost and robot size. Also, performs a tracking system with precision and robustness that can operate AVGs in an industrial environment. Artificial beacons detection algorithm combined with a Kalman filter and outliers rejection method increase the robustness and precision of the developed system. A comparison between the presented approach and a commercial localization system for industry is presented. Finally, the proposed algorithms were tested in an industrial application under realistic working conditions.

Abstract
Laser scanners are widely used in mobile robotics localization systems but, despite the enormous potential of its use, their high price tag is a major drawback, mainly for hobbyist and educational robotics practitioners that usually have a reduced budget. This paper presentes the modeling and simulation of a hacked Neato XV-11 Laser Scanner, having as motivation the fact that it is a very low cost alternative, when compared with the current available laser scanners. The modeling of a hacked Neato XV-11 Laser Scanner allows its realistic simulation and provides valuable information that can promote the development of better designs of robot localization systems based on this sensor. The sensor simulation was developed using SimTwo, which is a realistic simulation software that can support several types of robots.

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.