Marcelo Petry

Abstract
Inspection of railroad tracks is still predominantly performed visually by human inspectors. Due to the extension of the tracks this is a slow and tedious operation, significantly subjected to human errors and inconsistency. In this context, computer vision systems, composed of field-acquired images and processing algorithms, have a great potential to improve efficiency and to offer systematic inspection methodologies. In this paper the use of available point cloud and mesh generation algorithms to construct 3D surface of railroad tracks is investigated. To achieve this goal, images of a small track were acquired from several points-of-view. Next a comparison between several open and closed-source algorithms was performed, evaluating the number of 3D points, time consumption, RAM memory, GPU memory, number of faces, and the generated mesh. The results obtained demonstrate that with the right setup, current image processing methodologies can be used to construct 3D surfaces of uncontrolled scenarios, such as those of a real railroad environment. Regarding the comparison, SURE and Poisson presented the most accurate meshes. When comparing quantitative measures, though, Poisson presented a slightly better performance in time consumption, but SURE had a better RAM memory usage and a greater level of details. © 2017 IEEE.

Abstract
Nowadays, there are many technologies that support location systems involving intrusive and nonintrusive equipment and also varying in terms of precision, range, and cost. However, the developers some time neglect the noise introduced by these systems, which prevents these systems from reaching their full potential. Focused on this problem, in this research work a comparison study between three different filters was performed in order to reduce the noise introduced by a location system based on RFID UWB technology with an associated error of approximately 18 cm. To achieve this goal, a set of experiments was devised and executed using a miniature train moving at constant velocity in a scenario with two distinct shapes-linear and oval. Also, this train was equipped with a varying number of active tags. The obtained results proved that the Kalman Filter achieved better results when compared to the other two filters. Also, this filter increases the performance of the location system by 15% and 12% for the linear and oval paths respectively, when using one tag. For a multiple tags and oval shape similar results were obtained (11-13% of improvement).

Abstract
Most of the original image feature detectors are not able to cope with large photometric variations, and their extensions that should improve detection eventually increase the computational cost and introduce more noise to the system. Here we extend the original SURF algorithm increasing its invariance to illumination changes. Our approach uses the local space average color descriptor as working space to detect invariant features. A theoretical analysis demonstrates the impact of distinct photometric variations on the response of blob-like features detected with the SURF algorithm. Experimental results demonstrate the effectiveness of the approach in several illumination conditions including the presence of two or more distinct light sources, variations in color, in offset and scale.

Abstract
Intelligent wheelchairs can become an important solution to assist physically impaired individuals who find it difficult or impossible to drive regular powered wheelchairs. However, when designing the hardware architecture several projects compromise the user comfort and the wheelchair normal usability in order to solve robotic problems. In this paper we describe the main concepts regarding the design of the IntellWheels intelligent wheelchair. Our approach has a user-centered perspective, in which the needs and limitations of physically impaired users are given extensive attention at each stage of the design process. Finally, our design was evaluated through a public opinion assessment. A statistical analysis suggested that the design was effective to mitigate the visual and ergonomic impacts caused by the addition of sensorial and processing capabilities on the wheelchair. © 2013 IEEE.

Abstract
Assistive Technologies may greatly contribute to give autonomy and independence for individuals with physical limitations. Electric wheelchairs are examples of those assistive technologies and nowadays each time becoming more intelligent due to the use of technology that provides assisted safer driving. Usually, the user controls the electric wheelchair with a conventional analog joystick. However, this implies the need for an appropriate methodology to map the position of the joystick handle, in a Cartesian coordinate system, to the wheelchair wheels intended velocities. This mapping is very important since it will determine the response behavior of the wheelchair to the user manual control. This paper describes the implementation of several joystick mappings in an intelligent wheelchair (IW) prototype. Experiments were performed in a realistic simulator using cerebral palsy users with distinct driving abilities. The users had 6 different joystick control mapping methods and for each user the usability and the users' preference order was measured. The results achieved show that a linear mapping, with appropriate parameters, between the joystick's coordinates and the wheelchair wheel speeds is preferred by the majority of the users.