Abstract
In the past few years, cable-driven robots have received some attention by the scientific community and the industry. They have special characteristics that made them very reliable to operate with the level of safeness that is required by different environments, such as, handling of hazardous materials in construction sites. This paper presents a cable-driven robot called SPIDERobot, that was developed for automated construction of architectural projects. This robot has a rotating claw and it is controlled by a set of 4 cables that allow 4 degrees of freedom. In addition to the robot, this paper introduces a Dynamic Control System (DCS) that controls the positioning of the robot and assures that the length of cables is always within a safe value. Results show that traditional force-feasible approaches are more influenced by the pulling forces or the geometric arrangement of all cables and their positioning is significantly less accurate than the DCS. Therefore, the architecture of the SPIDERobot is designed to enable an easily scaling up of the solution to higher dimensions for operating in realistic environments.

Abstract
There are several approaches to create the Humanoid robot gait planning. This problem presents a large number of unknown parameters that should be found to make the humanoid robot to walk. Optimization in simulation models can be used to find the gait based on several criteria such as energy minimization, acceleration, step length among the others. The energy consumption can also be reduced with elastic elements coupled to each joint. The presented paper addresses an optimization method, the Stretched Simulated Annealing, that runs in an accurate and stable simulation model to find the optimal gait combined with elastic elements. Final results demonstrate that optimization is a valid gait planning technique.

Abstract
This paper describes a procedure applied to model DC motors. An example of the procedure apply is shown for a 12V brushed DC motor, equipped with a 29:1 metal gearbox and an integrated quadrature encoder. It is described the developed setup applied to obtain the experimental data and the developed algorithm applied to estimate the actuator parameters. It was obtained an electro-mechanical dynamical model that describes the motor, its gear box and the encoder. The motivation to develop a simple and easy to assemble procedure that allows to model DC motors is due to the fact that these actuators are intensively used in mobile robotics, being realistic simulation, based in accurate sensor and actuator models, the key to speed up Robot Software developing time.

Abstract
This research studies motion segmentation based on dense optical flow fields for mobile robotic applications. The optical flow is usually represented in the Euclidean space however, finding the most suitable motion space is a relevant problem because techniques for motion analysis have distinct performances. Factors like the processing-time and the quality of the segmentation provide a quantitative evaluation of the clustering process. Therefore, this paper defines a methodology that evaluates and compares the advantage of clustering dense flow fields using different feature spaces, for instance, Euclidean and Polar space. The methodology resorts to conventional clustering techniques, Expectation-Maximization and K-means, as baseline methods. The experiments conducted during this paper proved that the K-means clustering is suitable for analyzing dense flow fields.

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.