A grammatical approach to the modeling of an autonomous robot

Virtual Worlds Generator is a grammatical model that is proposed to define virtual worlds. It integrates the diversity of sensors and interaction devices, multimodality and a virtual simulation system. Its grammar allows the definition and abstraction in symbols strings of the scenes of the virtual world, independently of the hardware that is used to represent the world or to interact with it. A case study is presented to explain how to use the proposed model to formalize a robot navigation system with multimodal perception and a hybrid control scheme of the robot. The result is an instance of the model grammar that implements the robotic system and is independent of the sensing devices used for perception and interaction. As a conclusion the Virtual Worlds Generator adds value in the simulation of virtual worlds since the definition can be done formally and independently of the peculiarities of the supporting devices.

eFisioTrack: a telerehabilitation environment based on motion recognition using accelerometry

The growing demand for physical rehabilitation processes can result in the rising of costs and waiting lists, becoming a threat to healthcare services’ sustainability. Telerehabilitation solutions can help in this issue by discharging patients from points of care while improving their adherence to treatment. Sensing devices are used to collect data so that the physiotherapists can monitor and evaluate the patients’ activity in the scheduled sessions. This paper presents a software platform that aims to meet the needs of the rehabilitation experts and the patients along a physical rehabilitation plan, allowing its use in outpatient scenarios. It is meant to be low-cost and easy-to-use, improving patients and experts experience. We show the satisfactory results already obtained from its use, in terms of the accuracy evaluating the exercises, and the degree of users’ acceptance. We conclude that this platform is suitable and technically feasible to carry out rehabilitation plans outside the point of care.

Electrochemical behaviour of different redox probes on single wall carbon nanotube buckypaper-modified electrodes

In the present work, the electrochemical properties of single-walled carbon nanotube buckypapers (BPs) were examined in terms of carbon nanotubes nature and preparation conditions. The performance of the different free-standing single wall carbon nanotube sheets was evaluated via cyclic voltammetry of several redox probes in aqueous electrolyte. Significant differences are observed in the electron transfer kinetics of the buckypaper-modified electrodes for both the outer- and inner-sphere redox systems. These differences can be ascribed to the nature of the carbon nanotubes (nanotube diameter, chirality and aspect ratio), surface oxidation degree and type of functionalities. In the case of dopamine, ferrocene/ferrocenium, and quinone/hydroquinone redox systems the voltammetric response should be thought as a complex contribution of different tips and sidewall domains which act as mediators for the electron transfer between the adsorbate species and the molecules in solution. In the other redox systems only nanotube ends are active sites for the electron transfer. It is also interesting to point out that a higher electroactive surface area not always lead to an improvement in the electron transfer rate of various redox systems. In addition, the current densities produced by the redox reactions studied here are high enough to ensure a proper electrochemical signal, which enables the use of BPs in sensing devices.

3D visual sensing of human hand for remote operation of a robotic hand

New low cost sensors and open free libraries for 3D image processing are making important advances in robot vision applications possible, such as three-dimensional object recognition, semantic mapping, navigation and localization of robots, human detection and/or gesture recognition for human-machine interaction. In this paper, a novel method for recognizing and tracking the fingers of a human hand is presented. This method is based on point clouds from range images captured by a RGBD sensor. It works in real time and it does not require visual marks, camera calibration or previous knowledge of the environment. Moreover, it works successfully even when multiple objects appear in the scene or when the ambient light is changed. Furthermore, this method was designed to develop a human interface to control domestic or industrial devices, remotely. In this paper, the method was tested by operating a robotic hand. Firstly, the human hand was recognized and the fingers were detected. Secondly, the movement of the fingers was analysed and mapped to be imitated by a robotic hand.