Robotic ubiquitous cognitive ecology for smart homes

Robotic ecologies are networks of heterogeneous robotic devices pervasively embedded in everyday environments, where they cooperate to perform complex tasks. While their potential makes them increasingly popular, one fundamental problem is how to make them both autonomous and adaptive, so as to reduce the amount of preparation, pre-programming and human supervision that they require in real world applications. The project RUBICON develops learning solutions which yield cheaper, adaptive and efficient coordination of robotic ecologies. The approach we pursue builds upon a unique combination of methods from cognitive robotics, machine learning, planning and agent- based control, and wireless sensor networks. This paper illustrates the innovations advanced by RUBICON in each of these fronts before describing how the resulting techniques have been integrated and applied to a smart home scenario. The resulting system is able to provide useful services and pro-actively assist the users in their activities. RUBICON learns through an incremental and progressive approach driven by the feed- back received from its own activities and from the user, while also self-organizing the manner in which it uses available sensors, actuators and other functional components in the process. This paper summarises some of the lessons learned by adopting such an approach and outlines promising directions for future work

Ontology-based information extraction and reservoir computing for topic detection from blogosphere's content : a case study about BBC backstage

This research study aims at detecting topics and extracting themes(subtopics) from the blogosphere’s content while bridging the gap between the Social Web and the Semantic Web. The goal is to detect certain types of information from collections of blogs’ and microblogs’ narratives that lack explicit semantics. The approach presented introduces a novel approach that blends together two young paradigms: Ontology-Based Information Extraction (OBIE) and Reservoir Computing (RC). The novelty of the work lies in integrating ontologies and RC as well as the pioneering use of RC with social media data. Experiments with retrospect data from blogs and Twitter microblogs provide valuable insights into the BBC Backstage initiative and prove the viability of the approach presented in terms of scalability, computational complexity,and performance

Modelling of nonlinear effects and the response of ultrasound contrast micro bubbles: simulation and experiment

The propagation of diagnostic ultrasonic imaging pulses in tissue and their interaction with contrast micro bubbles is a very complex physical process, which we assumed to be separable into three stages: pulse propagation in tissue, the interaction of the pulse with the contrast bubble, and the propagation of the scattered echo. The model driven approach is used to gain better knowledge of the complex processes involved. A simplified way of field simulation is chosen due to the complexity of the task and the necessity to estimate comparative contributions of each component of the process. Simulations are targeted at myocardial perfusion estimation. A modified method for spatial superposition of attenuated waves enables simulations of low intensity pulse pressure fields from weakly focused transducers in a nonlinear, attenuating, and liquid-like biological medium. These assumptions enable the use of quasi-linear calculations of the acoustic field. The simulations of acoustic bubble response are carried out with the Rayleigh-Plesset equation with the addition of radiation damping. Theoretical simulations with synthesised and experimentally sampled pulses show that the interaction of the excitation pulses with the contrast bubbles is the main cause of nonlinear scattering, and a 2-3 dB increase of second harmonic amplitude depends on nonlinear distortions of the incident pulse. (C) 2004 Elsevier B.V. All rights reserved

3D microporous scaffolds manufactured via combination of fused filament fabrication and direct laser writing ablation

A 3D printing fused filament fabrication (FFF) approach has been implemented for the creation of microstructures having an internal 3D microstructure geometry. These objects were produced without any sacrificial structures or additional support materials, just by precisely tuning the nozzle heating, fan cooling and translation velocity parameters. The manufactured microporous structures out of polylactic acid (PLA) had fully controllable porosity (20%-60%) and consisted of desired volume pores (similar to 0.056 mu m(3)). The prepared scaffolds showed biocompatibility and were suitable for the primary stem cell growth. In addition, direct laser writing (DLW) ablation was employed to modify the surfaces of the PLA structures, drill holes, as well as shape the outer geometries of the created objects. The proposed combination of FFF printing with DLW offers successful fabrication of 3D microporous structures with functionalization capabilities, such as the modification of surfaces, the generation of grooves and microholes and cutting out precisely shaped structures (micro-arrows, micro-gears). The produced structures could serve as biomedical templates for cell culturing, as well as biodegradable implants for tissue engineering. The additional micro-architecture is important in connection with the cell types used for the intention of cell growing. Moreover, we show that surface roughness can be modified at the nanoscale by immersion into an acetone bath, thus increasing the hydrophilicity. The approach is not limited to biomedical applications, it could be employed for the manufacturing of bioresorbable 3D microfluidic and micromechanic structures