A mosaic of eyes

Autonomous navigation is a traditional research topic in intelligent robotics and vehicles, which requires a robot to perceive its environment through onboard sensors such as cameras or laser scanners, to enable it to drive to its goal. Most research to date has focused on the development of a large and smart brain to gain autonomous capability for robots. There are three fundamental questions to be answered by an autonomous mobile robot: 1) Where am I going? 2) Where am I? and 3) How do I get there? To answer these basic questions, a robot requires a massive spatial memory and considerable computational resources to accomplish perception, localization, path planning, and control. It is not yet possible to deliver the centralized intelligence required for our real-life applications, such as autonomous ground vehicles and wheelchairs in care centers. In fact, most autonomous robots try to mimic how humans navigate, interpreting images taken by cameras and then taking decisions accordingly. They may encounter the following difficulties

Landfill gas monitoring network - development of wireless sensor network platforms

A wireless sensor network has been developed for the application of landfill gas monitoring, specifically sensing methane, carbon dioxide and extraction pressure. This collaborative work with the Irish Environmental Protection Agency has been motivated by the need to reduce greenhouse gas emissions as well as aiming to improve landfill gas management and utilisation. This paper describes the preliminary findings of an ongoing trial deployment of multiple sensing platforms on an active landfill facility; data has been acquired for nine months to date. The platforms have operated successfully despite adverse on-site conditions, with validity demonstrated by reasonably strong correlation with independent on-site measurements. The increased temporal and spatial resolution provided by distributed sensor platforms is discussed with regard to improving landfill gas management practice

Design of a multiple bloom filter for distributed navigation routing

Unmanned navigation of vehicles and mobile robots can be greatly simplified by providing environmental intelligence with dispersed wireless sensors. The wireless sensors can work as active landmarks for vehicle localization and routing. However, wireless sensors are often resource scarce and require a resource-saving design. In this paper, a multiple Bloom-filter scheme is proposed to compress a global routing table for a wireless sensor. It is used as a lookup table for routing a vehicle to any destination but requires significantly less memory space and search effort. An error-expectation-based design for a multiple Bloom filter is proposed as an improvement to the conventional false-positive-rate-based design. The new design is shown to provide an equal relative error expectation for all branched paths, which ensures a better network load balance and uses less memory space. The scheme is implemented in a project for wheelchair navigation using wireless camera motes. © 2013 IEEE

Autonomous service composition in symbiotic networks

Part 2: PhD Workshop: Autonomic Network and Service ManagementInternational audienceTo cope with the ever-growing number of wired and wireless networks, we introduce the notion of so-called symbiotic networks. These networks seamlessly operate across layers and over network boundaries, resulting in improved scalability, dependability, and energy efficiency. This particular Ph.D. research focuses on software services operating in such symbiotic networks. When two or more networks merge, the services provided on them may be combined into a service composition that is much more than the sum of its parts. Driven by two distinct use cases, we aim to enable fully autonomous service composition and resource provisioning. For the first use case, an in-building over-the-top service platform, we describe a software architecture and a set of generic resource provisioning algorithms. The second use case, which focuses on wireless body area networks, will allow us to expand our research domain into highly dynamic symbiotic network environments, where services appear and disappear more frequently

Correlated shadowing and fading characterization of MIMO off-body channels by means of multiple autonomous on-body nodes

In off-body communication systems low-cost and compact transceivers are important for realistic applications. An autonomous off-body wireless node was designed and integrated onto a textile antenna. Channel measurements were performed for an indoor non line-off-sight 4x2 MIMO (Multiple-Input Multiple-Output) link using four off-body transmitting nodes and two similar fixed receiving nodes. The channel behavior is characterized as Rayleigh fading with lognormal shadowing and is fitted to a model determining fading and shadowing correlation matrices. The physics of the propagation is captured accurately by the model which is further used to simulate a link using diversity by means of Selection Combining, as implemented on the wireless nodes. The performance of measured and simulated links is compared in terms of outage probability level. The measurements and analysis confirm that the correlated shadowing and fading model is relevant for realistic off-body networks employing diversity by means of Selection Combining

Piezoelectric vibration energy harvesting from airflow in HVAC (Heating Ventilation and Air Conditioning) systems

This study focuses on the design and wind tunnel testing of a high efficiency Energy Harvesting device, based on piezoelectric materials, with possible applications for the sustainability of smart buildings, structures and infrastructures. The development of the device was supported by ESA (the European Space Agency) under a program for the space technology transfer in the period 2014-2016. The EH device harvests the airflow inside Heating, Ventilation and Air Conditioning (HVAC) systems, using a piezoelectric component and an appropriate customizable aerodynamic appendix or fin that takes advantage of specific airflow phenomena (vortex shedding and galloping), and can be implemented for optimizing the energy consumption inside buildings. Focus is given on several relevant aspects of wind tunnel testing: different configurations for the piezoelectric bender (rectangular, cylindrical and T-shaped) are tested and compared, and the effective energy harvesting potential of a working prototype device is assessed

Self-Stabilizing TDMA Algorithms for Dynamic Wireless Ad-hoc Networks

In dynamic wireless ad-hoc networks (DynWANs), autonomous computing devices set up a network for the communication needs of the moment. These networks require the implementation of a medium access control (MAC) layer. We consider MAC protocols for DynWANs that need to be autonomous and robust as well as have high bandwidth utilization, high predictability degree of bandwidth allocation, and low communication delay in the presence of frequent topological changes to the communication network. Recent studies have shown that existing implementations cannot guarantee the necessary satisfaction of these timing requirements. We propose a self-stabilizing MAC algorithm for DynWANs that guarantees a short convergence period, and by that, it can facilitate the satisfaction of severe timing requirements, such as the above. Besides the contribution in the algorithmic front of research, we expect that our proposal can enable quicker adoption by practitioners and faster deployment of DynWANs that are subject changes in the network topology

Distributed chemical sensor networks for environmental sensing

Society is increasingly accustomed to instant access to real-time information, due to the ubiquitous use of the internet and web-based access tools. Intelligent search engines enable huge data repositories to be searched, and highly relevant information returned in real time. These repositories increasingly include environmental information related to the environment, such as distributed air and water quality. However, while this information at present is typically historical, for example, through agency reports, there is increasing demand for real-time environmental data. In this paper, the issues involved in obtaining data from autonomous chemical sensors are discussed, and examples of current deployments presented. Strategies for achieving large-scale deployments are discussed

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