37,617 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 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
Multi-robot team formation control in the GUARDIANS project
Purpose
The GUARDIANS multi-robot team is to be deployed in a large warehouse in smoke. The team is to assist firefighters search the warehouse in the event or danger of a fire. The large dimensions of the environment together with development of smoke which drastically reduces visibility, represent major challenges for search and rescue operations. The GUARDIANS robots guide and accompany
the firefighters on site whilst indicating possible obstacles and the locations of danger and maintaining communications links.
Design/methodology/approach
In order to fulfill the aforementioned tasks the robots need to exhibit certain behaviours. Among the basic behaviours are capabilities to stay together as a
group, that is, generate a formation and navigate while keeping this formation.
The control model used to generate these behaviours is based on the so-called social potential field framework, which we adapt to the specific tasks required for the GUARDIANS scenario. All tasks can be achieved without central control, and some of the behaviours can be performed without explicit communication between the robots.
Findings
The GUARDIANS environment requires flexible formations of the robot team: the formation has to adapt itself to the circumstances. Thus the application has forced us to redefine the concept of a formation. Using the graph-theoretic terminology, we can say that a formation may be stretched out as a path or be compact as a star or wheel. We have implemented the developed behaviours in simulation environments as well as on real ERA-MOBI robots commonly referred to as Erratics. We discuss advantages and shortcomings of our model, based on the simulations as
well as on the implementation with a team of Erratics.</p
Cooperative localization for mobile agents: a recursive decentralized algorithm based on Kalman filter decoupling
We consider cooperative localization technique for mobile agents with
communication and computation capabilities. We start by provide and overview of
different decentralization strategies in the literature, with special focus on
how these algorithms maintain an account of intrinsic correlations between
state estimate of team members. Then, we present a novel decentralized
cooperative localization algorithm that is a decentralized implementation of a
centralized Extended Kalman Filter for cooperative localization. In this
algorithm, instead of propagating cross-covariance terms, each agent propagates
new intermediate local variables that can be used in an update stage to create
the required propagated cross-covariance terms. Whenever there is a relative
measurement in the network, the algorithm declares the agent making this
measurement as the interim master. By acquiring information from the interim
landmark, the agent the relative measurement is taken from, the interim master
can calculate and broadcast a set of intermediate variables which each robot
can then use to update its estimates to match that of a centralized Extended
Kalman Filter for cooperative localization. Once an update is done, no further
communication is needed until the next relative measurement
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