12,518 research outputs found
Robotic Wireless Sensor Networks
In this chapter, we present a literature survey of an emerging, cutting-edge,
and multi-disciplinary field of research at the intersection of Robotics and
Wireless Sensor Networks (WSN) which we refer to as Robotic Wireless Sensor
Networks (RWSN). We define a RWSN as an autonomous networked multi-robot system
that aims to achieve certain sensing goals while meeting and maintaining
certain communication performance requirements, through cooperative control,
learning and adaptation. While both of the component areas, i.e., Robotics and
WSN, are very well-known and well-explored, there exist a whole set of new
opportunities and research directions at the intersection of these two fields
which are relatively or even completely unexplored. One such example would be
the use of a set of robotic routers to set up a temporary communication path
between a sender and a receiver that uses the controlled mobility to the
advantage of packet routing. We find that there exist only a limited number of
articles to be directly categorized as RWSN related works whereas there exist a
range of articles in the robotics and the WSN literature that are also relevant
to this new field of research. To connect the dots, we first identify the core
problems and research trends related to RWSN such as connectivity,
localization, routing, and robust flow of information. Next, we classify the
existing research on RWSN as well as the relevant state-of-the-arts from
robotics and WSN community according to the problems and trends identified in
the first step. Lastly, we analyze what is missing in the existing literature,
and identify topics that require more research attention in the future
A decentralized motion coordination strategy for dynamic target tracking
This paper presents a decentralized motion planning
algorithm for the distributed sensing of a noisy dynamical
process by multiple cooperating mobile sensor agents. This
problem is motivated by localization and tracking tasks of
dynamic targets. Our gradient-descent method is based on a
cost function that measures the overall quality of sensing. We
also investigate the role of imperfect communication between
sensor agents in this framework, and examine the trade-offs in
performance between sensing and communication. Simulations
illustrate the basic characteristics of the algorithms
Markov Decision Processes with Applications in Wireless Sensor Networks: A Survey
Wireless sensor networks (WSNs) consist of autonomous and resource-limited
devices. The devices cooperate to monitor one or more physical phenomena within
an area of interest. WSNs operate as stochastic systems because of randomness
in the monitored environments. For long service time and low maintenance cost,
WSNs require adaptive and robust methods to address data exchange, topology
formulation, resource and power optimization, sensing coverage and object
detection, and security challenges. In these problems, sensor nodes are to make
optimized decisions from a set of accessible strategies to achieve design
goals. This survey reviews numerous applications of the Markov decision process
(MDP) framework, a powerful decision-making tool to develop adaptive algorithms
and protocols for WSNs. Furthermore, various solution methods are discussed and
compared to serve as a guide for using MDPs in WSNs
Routing Unmanned Vehicles in GPS-Denied Environments
Most of the routing algorithms for unmanned vehicles, that arise in data
gathering and monitoring applications in the literature, rely on the Global
Positioning System (GPS) information for localization. However, disruption of
GPS signals either intentionally or unintentionally could potentially render
these algorithms not applicable. In this article, we present a novel method to
address this difficulty by combining methods from cooperative localization and
routing. In particular, the article formulates a fundamental combinatorial
optimization problem to plan routes for an unmanned vehicle in a GPS-restricted
environment while enabling localization for the vehicle. We also develop
algorithms to compute optimal paths for the vehicle using the proposed
formulation. Extensive simulation results are also presented to corroborate the
effectiveness and performance of the proposed formulation and algorithms.Comment: Publised in International Conference on Umanned Aerial System
Assistance strategies for robotized laparoscopy
Robotizing laparoscopic surgery not only allows achieving better
accuracy to operate when a scale factor is applied between master and slave or thanks to the use of tools with 3 DoF, which cannot be used in conventional manual surgery, but also due to additional informatic support. Relying on computer assistance different strategies that facilitate the task of the surgeon can be incorporated, either in the form of autonomous navigation or cooperative guidance, providing sensory or visual feedback, or introducing certain limitations of movements. This paper describes different ways of assistance aimed at improving the work capacity of the surgeon and achieving more safety for the patient, and the results obtained with the prototype developed at UPC.Peer ReviewedPostprint (author's final draft
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