992 research outputs found
Black Hole Search with Finite Automata Scattered in a Synchronous Torus
We consider the problem of locating a black hole in synchronous anonymous
networks using finite state agents. A black hole is a harmful node in the
network that destroys any agent visiting that node without leaving any trace.
The objective is to locate the black hole without destroying too many agents.
This is difficult to achieve when the agents are initially scattered in the
network and are unaware of the location of each other. Previous studies for
black hole search used more powerful models where the agents had non-constant
memory, were labelled with distinct identifiers and could either write messages
on the nodes of the network or mark the edges of the network. In contrast, we
solve the problem using a small team of finite-state agents each carrying a
constant number of identical tokens that could be placed on the nodes of the
network. Thus, all resources used in our algorithms are independent of the
network size. We restrict our attention to oriented torus networks and first
show that no finite team of finite state agents can solve the problem in such
networks, when the tokens are not movable. In case the agents are equipped with
movable tokens, we determine lower bounds on the number of agents and tokens
required for solving the problem in torus networks of arbitrary size. Further,
we present a deterministic solution to the black hole search problem for
oriented torus networks, using the minimum number of agents and tokens
Gathering in Dynamic Rings
The gathering problem requires a set of mobile agents, arbitrarily positioned
at different nodes of a network to group within finite time at the same
location, not fixed in advanced.
The extensive existing literature on this problem shares the same fundamental
assumption: the topological structure does not change during the rendezvous or
the gathering; this is true also for those investigations that consider faulty
nodes. In other words, they only consider static graphs. In this paper we start
the investigation of gathering in dynamic graphs, that is networks where the
topology changes continuously and at unpredictable locations.
We study the feasibility of gathering mobile agents, identical and without
explicit communication capabilities, in a dynamic ring of anonymous nodes; the
class of dynamics we consider is the classic 1-interval-connectivity.
We focus on the impact that factors such as chirality (i.e., a common sense
of orientation) and cross detection (i.e., the ability to detect, when
traversing an edge, whether some agent is traversing it in the other
direction), have on the solvability of the problem. We provide a complete
characterization of the classes of initial configurations from which the
gathering problem is solvable in presence and in absence of cross detection and
of chirality. The feasibility results of the characterization are all
constructive: we provide distributed algorithms that allow the agents to
gather. In particular, the protocols for gathering with cross detection are
time optimal. We also show that cross detection is a powerful computational
element.
We prove that, without chirality, knowledge of the ring size is strictly more
powerful than knowledge of the number of agents; on the other hand, with
chirality, knowledge of n can be substituted by knowledge of k, yielding the
same classes of feasible initial configurations
Towards formal models and languages for verifiable Multi-Robot Systems
Incorrect operations of a Multi-Robot System (MRS) may not only lead to
unsatisfactory results, but can also cause economic losses and threats to
safety. These threats may not always be apparent, since they may arise as
unforeseen consequences of the interactions between elements of the system.
This call for tools and techniques that can help in providing guarantees about
MRSs behaviour. We think that, whenever possible, these guarantees should be
backed up by formal proofs to complement traditional approaches based on
testing and simulation.
We believe that tailored linguistic support to specify MRSs is a major step
towards this goal. In particular, reducing the gap between typical features of
an MRS and the level of abstraction of the linguistic primitives would simplify
both the specification of these systems and the verification of their
properties. In this work, we review different agent-oriented languages and
their features; we then consider a selection of case studies of interest and
implement them useing the surveyed languages. We also evaluate and compare
effectiveness of the proposed solution, considering, in particular, easiness of
expressing non-trivial behaviour.Comment: Changed formattin
A framework for proving the self-organization of dynamic systems
This paper aims at providing a rigorous definition of self- organization, one
of the most desired properties for dynamic systems (e.g., peer-to-peer systems,
sensor networks, cooperative robotics, or ad-hoc networks). We characterize
different classes of self-organization through liveness and safety properties
that both capture information re- garding the system entropy. We illustrate
these classes through study cases. The first ones are two representative P2P
overlays (CAN and Pas- try) and the others are specific implementations of
\Omega (the leader oracle) and one-shot query abstractions for dynamic
settings. Our study aims at understanding the limits and respective power of
existing self-organized protocols and lays the basis of designing robust
algorithm for dynamic systems
Past, Present, and Future of Simultaneous Localization And Mapping: Towards the Robust-Perception Age
Simultaneous Localization and Mapping (SLAM)consists in the concurrent
construction of a model of the environment (the map), and the estimation of the
state of the robot moving within it. The SLAM community has made astonishing
progress over the last 30 years, enabling large-scale real-world applications,
and witnessing a steady transition of this technology to industry. We survey
the current state of SLAM. We start by presenting what is now the de-facto
standard formulation for SLAM. We then review related work, covering a broad
set of topics including robustness and scalability in long-term mapping, metric
and semantic representations for mapping, theoretical performance guarantees,
active SLAM and exploration, and other new frontiers. This paper simultaneously
serves as a position paper and tutorial to those who are users of SLAM. By
looking at the published research with a critical eye, we delineate open
challenges and new research issues, that still deserve careful scientific
investigation. The paper also contains the authors' take on two questions that
often animate discussions during robotics conferences: Do robots need SLAM? and
Is SLAM solved
On the Role of Mobility for Multi-message Gossip
We consider information dissemination in a large -user wireless network in
which users wish to share a unique message with all other users. Each of
the users only has knowledge of its own contents and state information;
this corresponds to a one-sided push-only scenario. The goal is to disseminate
all messages efficiently, hopefully achieving an order-optimal spreading rate
over unicast wireless random networks. First, we show that a random-push
strategy -- where a user sends its own or a received packet at random -- is
order-wise suboptimal in a random geometric graph: specifically,
times slower than optimal spreading. It is known that this
gap can be closed if each user has "full" mobility, since this effectively
creates a complete graph. We instead consider velocity-constrained mobility
where at each time slot the user moves locally using a discrete random walk
with velocity that is much lower than full mobility. We propose a simple
two-stage dissemination strategy that alternates between individual message
flooding ("self promotion") and random gossiping. We prove that this scheme
achieves a close to optimal spreading rate (within only a logarithmic gap) as
long as the velocity is at least . The key
insight is that the mixing property introduced by the partial mobility helps
users to spread in space within a relatively short period compared to the
optimal spreading time, which macroscopically mimics message dissemination over
a complete graph.Comment: accepted to IEEE Transactions on Information Theory, 201
The robustness of democratic consensus
In linear models of consensus dynamics, the state of the various agents
converges to a value which is a convex combination of the agents' initial
states. We call it democratic if in the large scale limit (number of agents
going to infinity) the vector of convex weights converges to 0 uniformly.
Democracy is a relevant property which naturally shows up when we deal with
opinion dynamic models and cooperative algorithms such as consensus over a
network: it says that each agent's measure/opinion is going to play a
negligeable role in the asymptotic behavior of the global system. It can be
seen as a relaxation of average consensus, where all agents have exactly the
same weight in the final value, which becomes negligible for a large number of
agents.Comment: 13 pages, 2 fig
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