4,572 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
Accurate position tracking with a single UWB anchor
Accurate localization and tracking are a fundamental requirement for robotic
applications. Localization systems like GPS, optical tracking, simultaneous
localization and mapping (SLAM) are used for daily life activities, research,
and commercial applications. Ultra-wideband (UWB) technology provides another
venue to accurately locate devices both indoors and outdoors. In this paper, we
study a localization solution with a single UWB anchor, instead of the
traditional multi-anchor setup. Besides the challenge of a single UWB ranging
source, the only other sensor we require is a low-cost 9 DoF inertial
measurement unit (IMU). Under such a configuration, we propose continuous
monitoring of UWB range changes to estimate the robot speed when moving on a
line. Combining speed estimation with orientation estimation from the IMU
sensor, the system becomes temporally observable. We use an Extended Kalman
Filter (EKF) to estimate the pose of a robot. With our solution, we can
effectively correct the accumulated error and maintain accurate tracking of a
moving robot.Comment: Accepted by ICRA202
Distributed Algorithms for Stochastic Source Seeking With Mobile Robot Networks
Autonomous robot networks are an effective tool for monitoring large-scale environmental fields. This paper proposes distributed control strategies for localizing the source of a noisy signal, which could represent a physical quantity of interest such as magnetic force, heat, radio signal, or chemical concentration. We develop algorithms specific to two scenarios: one in which the sensors have a precise model of the signal formation process and one in which a signal model is not available. In the model-free scenario, a team of sensors is used to follow a stochastic gradient of the signal field. Our approach is distributed, robust to deformations in the group geometry, does not necessitate global localization, and is guaranteed to lead the sensors to a neighborhood of a local maximum of the field. In the model-based scenario, the sensors follow a stochastic gradient of the mutual information (MI) between their expected measurements and the expected source location in a distributed manner. The performance is demonstrated in simulation using a robot sensor network to localize the source of a wireless radio signal
Particle Swarm Optimization Based Source Seeking
Signal source seeking using autonomous vehicles is a complex problem. The
complexity increases manifold when signal intensities captured by physical
sensors onboard are noisy and unreliable. Added to the fact that signal
strength decays with distance, noisy environments make it extremely difficult
to describe and model a decay function. This paper addresses our work with
seeking maximum signal strength in a continuous electromagnetic signal source
with mobile robots, using Particle Swarm Optimization (PSO). A one to one
correspondence with swarm members in a PSO and physical Mobile robots is
established and the positions of the robots are iteratively updated as the PSO
algorithm proceeds forward. Since physical robots are responsive to swarm
position updates, modifications were required to implement the interaction
between real robots and the PSO algorithm. The development of modifications
necessary to implement PSO on mobile robots, and strategies to adapt to real
life environments such as obstacles and collision objects are presented in this
paper. Our findings are also validated using experimental testbeds.Comment: 13 pages, 12 figure
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