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
The research proposes a novel technological solution for marker-based human motion capture called WirelessSyncroVision (WSV). The WSV is formed by two main modules: the visual node (WSV-V) which is based on a stereoscopic vision system and the marker node (WSV-M) that is constituted by a 6-DOF active marker. The solution synchronizes the acquisition of images in remote muti-cameras with the ON period of the active marker. This increases the robustness of the stereoscopic system to illumination changes, which is extremely relevant for programming industrial robotic-arms using a human demonstrator programming by demonstration (PbD). In addition, the research presents a robust method named Adaptive and Robust Synchronization (ARS), that is designed for temporal alignment of remote devices using a wireless network. The algorithm models the phase difference as a function of time, measuring the parameters that must be known to predict the synchronization instant between the active marker and the remote cameras. Results demonstrate that the ARS creates a balance between the real-time capability and the performance estimation of the phase difference. Therefore, this research proposes an elegant solution to synchronize image acquisition systems in real-time that is easy to implement with low operational costs; however, the major advantage of the WSV is related to its high level of flexibility since it can be extended toward to other devices besides the PbD, for instance, motion capture, motion analysis, and remote sensoring systems.

Abstract
Robotic autonomous driving is a very complex task that tries to replicate the human behavior when performing such task. This paper presents a high-level overview of an architecture applicable for small-scale vehicles in autonomous driving competitions. A special emphasis is given on the sensory and navigation sub-systems since they are the most prominent intelligent decision layers. The former is almost entirely based on computer vision, processing the raw image content from two ordinary and inexpensive "web-cams", conveying further relevant information to the later, on a real-time basis. The proposed architecture was implemented with minimal interventions to an Ackermann-like vehicle which was originally designed for recreational purposes, serving as a "proof of concept" of the developed system. Results show that a low-cost, scalable and modular system can be easily integrated on regular small-scale vehicles obtaining exciting results at a minimal cost.

Abstract
For docking manoeuvres, the detection of the objects to dock needs to be precise as the minimum deviation from the objective may lead to the failure of this task. The objective of this article is to test possible ways to detect a landmark using a laser rangefinder for docking manoeuvres. We will test a beacon-based localisation algorithm and an algorithm based on natural landmarks already implemented, however, we will apply modifications to such methods. To verify the possibility of docking using these methods, we will conduct experiments with a real robot. © Springer International Publishing AG 2018.

Abstract
In this paper we introduce the problem of planning for perception of a target position. Given a sensing target, the robot has to move to a goal position from where the target can be perceived. Our algorithm minimizes the overall path cost as a function of both motion and perception costs, given an initial robot position and a sensing target. We contribute a heuristic search method, PA*, that efficiently searches for an optimal path. We prove the proposed heuristic is admissible, and introduce a new goal state stopping condition.

Abstract
Wheelchairs are important locomotion devices for handicapped and senior people. With the increase in the number of senior citizens and the increment of people bearing physical deficiencies, there is a growing demand for safer and more comfortable wheelchairs. So the new Intelligent Wheelchair (IW) concept was introduced. Like many other robotic systems, the main capabilities of an intelligent wheelchair should be: autonomous navigation with safety, flexibility and capability of avoiding obstacles; intelligent interface with the user; communication with other devices. In order to achieve these capabilities a good testbed is needed on which trials and users' training may be safely conducted. This paper presents an extensible virtual environment simulator of an intelligent wheelchair to fulfill that purpose. The simulator combines the main features of robotic simulators with those built for training and evaluation of prospective wheelchair users. Experiments with the real prototype allowed having results and information to model the virtual intelligent wheelchair. Several experiments with real users of electric wheelchairs (suffering from cerebral palsy) and potential users of an intelligent wheelchair were performed. The System Usability Score allowed having the perception of the users in terms of the usability of the IW in the virtual environment. The mean score was 72 indicating a satisfactory level of the usability. It was possible to conclude with the experiments that the virtual intelligent wheelchair and environment are usable instruments to test and train potential users.