3,704 research outputs found
Living IoT: A Flying Wireless Platform on Live Insects
Sensor networks with devices capable of moving could enable applications
ranging from precision irrigation to environmental sensing. Using mechanical
drones to move sensors, however, severely limits operation time since flight
time is limited by the energy density of current battery technology. We explore
an alternative, biology-based solution: integrate sensing, computing and
communication functionalities onto live flying insects to create a mobile IoT
platform.
Such an approach takes advantage of these tiny, highly efficient biological
insects which are ubiquitous in many outdoor ecosystems, to essentially provide
mobility for free. Doing so however requires addressing key technical
challenges of power, size, weight and self-localization in order for the
insects to perform location-dependent sensing operations as they carry our IoT
payload through the environment. We develop and deploy our platform on
bumblebees which includes backscatter communication, low-power
self-localization hardware, sensors, and a power source. We show that our
platform is capable of sensing, backscattering data at 1 kbps when the insects
are back at the hive, and localizing itself up to distances of 80 m from the
access points, all within a total weight budget of 102 mg.Comment: Co-primary authors: Vikram Iyer, Rajalakshmi Nandakumar, Anran Wang,
In Proceedings of Mobicom. ACM, New York, NY, USA, 15 pages, 201
A robot swarm assisting a human fire-fighter
Emergencies in industrial warehouses are a major concern for fire-fighters. The large dimensions, together with the development of dense smoke that drastically reduces visibility, represent major challenges. The GUARDIANS robot swarm is designed to assist fire-fighters in searching a large warehouse. In this paper we discuss the technology developed for a swarm of robots assisting fire-fighters. We explain the swarming algorithms that provide the functionality by which the robots react to and follow humans while no communication is required. Next we discuss the wireless communication system, which is a so-called mobile ad-hoc network. The communication network provides also the means to locate the robots and humans. Thus, the robot swarm is able to provide guidance information to the humans. Together with the fire-fighters we explored how the robot swarm should feed information back to the human fire-fighter. We have designed and experimented with interfaces for presenting swarm-based information to human beings
Data-Driven Grasp Synthesis - A Survey
We review the work on data-driven grasp synthesis and the methodologies for
sampling and ranking candidate grasps. We divide the approaches into three
groups based on whether they synthesize grasps for known, familiar or unknown
objects. This structure allows us to identify common object representations and
perceptual processes that facilitate the employed data-driven grasp synthesis
technique. In the case of known objects, we concentrate on the approaches that
are based on object recognition and pose estimation. In the case of familiar
objects, the techniques use some form of a similarity matching to a set of
previously encountered objects. Finally for the approaches dealing with unknown
objects, the core part is the extraction of specific features that are
indicative of good grasps. Our survey provides an overview of the different
methodologies and discusses open problems in the area of robot grasping. We
also draw a parallel to the classical approaches that rely on analytic
formulations.Comment: 20 pages, 30 Figures, submitted to IEEE Transactions on Robotic
Cooperative strategies for the detection and localization of odorants with robots and artificial noses
En este trabajo de investigación se aborda el diseño de una plataforma robótica
orientada a la implementación de estrategias de búsqueda cooperativa bioinspiradas.
En particular, tanto el proceso de diseño de la parte electrónica como
hardware se han enfocado hacia la validación en entornos reales de algoritmos
capaces de afrontar problemas de búsqueda con incertidumbre, como lo es la búsqueda
de fuentes de olor que presentan variación espacial y temporal. Este tipo
de problemas pueden ser resueltos de forma más eficiente con el empleo de enjambres
con una cantidad razonable de robots, y por tanto la plataforma ha sido
desarrollada utilizando componentes de bajo coste. Esto ha sido posible por la
combinación de elementos estandarizados -como la placa controladora Arduino
y otros sensores integrados- con piezas que pueden ser fabricadas mediante una
impresora 3D atendiendo a la filosofía del hardware libre (open-source).
Entre los requisitos de diseño se encuentran además la eficiencia energética
-para maximizar el tiempo de funcionamiento de los robots-, su capacidad de
posicionamiento en el entorno de búsqueda, y la integración multisensorial -con la
inclusión de una nariz electrónica, sensores de luminosidad, distancia, humedad
y temperatura, así como una brújula digital-. También se aborda el uso de una
estrategia de comunicación adecuada basada en ZigBee. El sistema desarrollado,
denominado GNBot, se ha validado tanto en los aspectos de eficiencia energética
como en sus capacidades combinadas de posicionamiento espacial y de detección
de fuentes de olor basadas en disoluciones de etanol.
La plataforma presentada -formada por el GNBot, su placa electrónica GNBoard
y la capa de abstracción software realizada en Python- simplificará por
tanto el proceso de implementación y evaluación de diversas estrategias de detección,
búsqueda y monitorización de odorantes, con la estandarización de enjambres
de robots provistos de narices artificiales y otros sensores multimodales.This research work addresses the design of a robotic platform oriented towards
the implementation of bio-inspired cooperative search strategies. In particular, the
design processes of both the electronics and hardware have been focused towards
the real-world validation of algorithms that are capable of tackling search problems
that have uncertainty, such as the search of odor sources that have spatio-temporal
variability. These kind of problems can be solved more efficiently with the use of
swarms formed by a considerable amount of robots, and thus the proposed platform
makes use of low cost components. This has been possible with the combination
of standardized elements -as the Arduino controller board and other integrated
sensors- with custom parts that can be manufactured with a 3D printer attending
to the open-source hardware philosophy.
Among the design requirements is the energy efficiency -in order to maximize
the working range of the robots-, their positioning capability within the search environment,
and multiple sensor integration -with the incorporation of an artificial
nose, luminosity, distance, humidity and temperature sensors, as well as an electronic
compass-. Another subject that is tackled is the use of an efficient wireless
communication strategy based on ZigBee. The developed system, named GNBot,
has also been validated in the aspects of energy efficiency and for its combined capabilities
for autonomous spatial positioning and detection of ethanol-based odor
sources.
The presented platform -formed by the GNBot, the GNBoard electronics and
the abstraction layer built in Python- will thus simplify the processes of implementation
and evaluation of various strategies for the detection, search and monitoring
of odorants with conveniently standardized robot swarms provided with artificial
noses and other multimodal sensors
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