Abstract
Visual motion perception from a moving observer is the most often encountered case in real life situations. It is a complex and challenging problem, although, it can promote the arising of new applications. This article presents an innovative and autonomous robotic system designed for active surveillance and a dense optical flow technique. Several optical flow techniques have been proposed for motion perception however, most of them are too computationally demanding for autonomous mobile systems. The proposed HybridTree method is able to identify the intrinsic nature of the motion by performing two consecutive operations: expectation and sensing. Descriptive properties of the image are retrieved using a tree-based scheme and during the expectation phase. In the sensing operation, the properties of image regions are used by a hybrid and hierarchical optical flow structure to estimate the flow field. The experiments prove that the proposed method extracts reliable visual motion information in a short period of time and is more suitable for applications that do not have specialized computer devices. Therefore, the HybridTree differs from other techniques since it introduces a new perspective for the motion perception computation: high level information about the image sequence is integrated into the estimation of the optical flow. In addition, it meets most of the robotic or surveillance demands and the resulting flow field is less computationally demanding comparatively to other state-of-the-art methods.

Abstract
Over the last few decades, surveillance applications have been an extremely useful tool to prevent dangerous situations and to identify abnormal activities. Although, the majority of surveillance videos are often subjected to different noises that corrupt structured patterns and fine edges. This makes the image processing methods even more difficult, for instance, object detection, motion segmentation, tracking, identification and recognition of humans. This paper proposes a novel filtering technique named robust bilateral and temporal (RBLT), which resorts to a spatial and temporal evolution of sequences to conduct the filtering process while preserving relevant image information. A pixel value is estimated using a robust combination of spatial characteristics of the pixel's neighborhood and its own temporal evolution. Thus, robust statics concepts and temporal correlation between consecutive images are incorporated together which results in a reliable and configurable filter formulation that makes it possible to reconstruct highly dynamic and degraded image sequences. The filtering is evaluated using qualitative judgments and several assessment metrics, for different Gaussian and Salt Pepper noise conditions. Extensive experiments considering videos obtained by stationary and non-stationary cameras prove that the proposed technique achieves a good perceptual quality of filtering sequences corrupted with a strong noise component.

Abstract
The simulation of a robot with a high number of joints can easily become unstable. Numerical errors on the first joint of the chain are propagated to the other joints. This is a very common problem in humanoid robots. A way to plan the gait for these robots is using simulation and optimization techniques. This paper addresses a new approach to optimizing gait parameter sets using an adaptive simulated annealing optimization algorithm, combined with a new joint model that reduces its instability. The new model and the optimization are implemented in SimTwo (a developed physical robot simulator that is capable of simulating user defined robots in a three-dimensional space, since it includes a physical model based on rigid body dynamics) and results are shown that validate the approach.

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 presented paper addresses a comparison between two optimization methods, the Stretched Simulated Annealing and the Genetic Algorithm, that runs in an accurate and stable simulation model. Final results show the comparative study and demonstrate that optimization is a valid gait planning technique.

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. At the same time, simulation has becoming more and more used in industries and academia since it presents several advantages. It takes the building and rebuilding phase out of the loop by using the model already created in the design phase. Further, simulation time on testing is cheaper and faster than performing the multiple tests of the design each time. Besides, it is easier to measure some variables in simulation than in real scenarios. In this paper, a laser scanner sensor is modeled and implemented in a developed simulator that already has several other sensors and actuators models. The presented simulation reflects the laser model properties such as target color dependences, noise, limits, time constraints, and target angle functions. As a case study, the same scenario is assembled with real components on a conveyer belt and in simulation. Results from both approaches are compared and validate the proposed model methodology. As an example, a 3D object recognition task is addressed highlighting the developed realistic model. Further industrial and R&D implementations based on this sensor could be stressed in simulation before implementation. © Springer International Publishing Switzerland 2013.

Abstract
This paper describes the EMG30 mechanical and electrical modeling and its simulation resorting to SimTwo (Robot@Factory mobile robot competition official simulator). It is described the developed setup applied to obtain the experimental data that was used 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 model and simulate the EMG30 is the fact that it is an actuator worldwide popular in the mobile robotics domain, being a low cost 12v motor equipped with encoders and a 30:1 reduction gearbox. The Goal of this work is to provide more realism and new features to the Robot@Factory official simulator, allowing participating teams to produce and validate different robot prototypes and its software, reducing considerably the development time. © Springer International Publishing Switzerland 2013.