1,440 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
Acoustic Communication for Medical Nanorobots
Communication among microscopic robots (nanorobots) can coordinate their
activities for biomedical tasks. The feasibility of in vivo ultrasonic
communication is evaluated for micron-size robots broadcasting into various
types of tissues. Frequencies between 10MHz and 300MHz give the best tradeoff
between efficient acoustic generation and attenuation for communication over
distances of about 100 microns. Based on these results, we find power available
from ambient oxygen and glucose in the bloodstream can readily support
communication rates of about 10,000 bits/second between micron-sized robots. We
discuss techniques, such as directional acoustic beams, that can increase this
rate. The acoustic pressure fields enabling this communication are unlikely to
damage nearby tissue, and short bursts at considerably higher power could be of
therapeutic use.Comment: added discussion of communication channel capacity in section
Social Cue Analysis using Transfer Entropy
Robots that work close to humans need to understand and use social cues to
act in a socially acceptable manner. Social cues are a form of communication
(i.e., information flow) between people. In this paper, a framework is
introduced to detect and analyse social cues and information transfer
directionality using an information-theoretic measure, namely, transfer
entropy. We demonstrate the framework in three settings involving social
interactions between humans: object-handover, group-joining and
person-following. Results show that transfer entropy can identify information
flows between agents, when and where they occur, and their relative strength.
For instance, in a person-following scenario, we find that head orientation of
a predictor is particularly informative, and the different times and locations
that this is used to convey information to a leader influences their behaviour.
Potential applications of the framework include information flow or social cue
analysis for interactive robot design, or socially-aware robot planning.Comment: 8 pages, 9 figures. Preprin
Guaranteeing Spoof-Resilient Multi-Robot Networks
Multi-robot networks use wireless communication to provide wide-ranging services such as aerial surveillance and unmanned delivery. However, effective coordination between multiple robots requires trust, making them particularly vulnerable to cyber-attacks. Specifically, such networks can be gravely disrupted by the Sybil attack, where even a single malicious robot can spoof a large number of fake clients. This paper proposes a new solution to defend against the Sybil attack, without requiring expensive cryptographic key-distribution. Our core contribution is a novel algorithm implemented on commercial Wi-Fi radios that can "sense" spoofers using the physics of wireless signals. We derive theoretical guarantees on how this algorithm bounds the impact of the Sybil Attack on a broad class of robotic coverage problems. We experimentally validate our claims using a team of AscTec quadrotor servers and iRobot Create ground clients, and demonstrate spoofer detection rates over 96%
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