539 research outputs found
Gathering on a Circle with Limited Visibility by Anonymous Oblivious Robots
A swarm of anonymous oblivious mobile robots, operating in deterministic Look-Compute-Move cycles, is confined within a circular track. All robots agree on the clockwise direction (chirality), they are activated by an adversarial semi-synchronous scheduler (SSYNCH), and an active robot always reaches the destination point it computes (rigidity). Robots have limited visibility: each robot can see only the points on the circle that have an angular distance strictly smaller than a constant ϑ from the robot’s current location, where 0 < ϑ ≤ π (angles are expressed in radians). We study the Gathering problem for such a swarm of robots: that is, all robots are initially in distinct locations on the circle, and their task is to reach the same point on the circle in a finite number of turns, regardless of the way they are activated by the scheduler. Note that, due to the anonymity of the robots, this task is impossible if the initial configuration is rotationally symmetric; hence, we have to make the assumption that the initial configuration be rotationally asymmetric. We prove that, if ϑ = π (i.e., each robot can see the entire circle except its antipodal point), there is a distributed algorithm that solves the Gathering problem for swarms of any size. By contrast, we also prove that, if ϑ ≤ π/2, no distributed algorithm solves the Gathering problem, regardless of the size of the swarm, even under the assumption that the initial configuration is rotationally asymmetric and the visibility graph of the robots is connected. The latter impossibility result relies on a probabilistic technique based on random perturbations, which is novel in the context of anonymous mobile robots. Such a technique is of independent interest, and immediately applies to other Pattern-Formation problems
Plane Formation by Synchronous Mobile Robots in the Three Dimensional Euclidean Space
Creating a swarm of mobile computing entities frequently called robots,
agents or sensor nodes, with self-organization ability is a contemporary
challenge in distributed computing. Motivated by this, we investigate the plane
formation problem that requires a swarm of robots moving in the three
dimensional Euclidean space to land on a common plane. The robots are fully
synchronous and endowed with visual perception. But they do not have
identifiers, nor access to the global coordinate system, nor any means of
explicit communication with each other. Though there are plenty of results on
the agreement problem for robots in the two dimensional plane, for example, the
point formation problem, the pattern formation problem, and so on, this is the
first result for robots in the three dimensional space. This paper presents a
necessary and sufficient condition for fully-synchronous robots to solve the
plane formation problem that does not depend on obliviousness i.e., the
availability of local memory at robots. An implication of the result is
somewhat counter-intuitive: The robots cannot form a plane from most of the
semi-regular polyhedra, while they can form a plane from every regular
polyhedron (except a regular icosahedron), whose symmetry is usually considered
to be higher than any semi-regular polyhedrdon
Getting Close Without Touching: Near-Gathering for Autonomous Mobile Robots
In this paper we study the Near-Gathering problem for a finite set of
dimensionless, deterministic, asynchronous, anonymous, oblivious and autonomous
mobile robots with limited visibility moving in the Euclidean plane in
Look-Compute-Move (LCM) cycles. In this problem, the robots have to get close
enough to each other, so that every robot can see all the others, without
touching (i.e., colliding with) any other robot. The importance of solving the
Near-Gathering problem is that it makes it possible to overcome the restriction
of having robots with limited visibility. Hence it allows to exploit all the
studies (the majority, actually) done on this topic in the unlimited visibility
setting. Indeed, after the robots get close enough to each other, they are able
to see all the robots in the system, a scenario that is similar to the one
where the robots have unlimited visibility.
We present the first (deterministic) algorithm for the Near-Gathering
problem, to the best of our knowledge, which allows a set of autonomous mobile
robots to nearly gather within finite time without ever colliding. Our
algorithm assumes some reasonable conditions on the input configuration (the
Near-Gathering problem is easily seen to be unsolvable in general). Further,
all the robots are assumed to have a compass (hence they agree on the "North"
direction), but they do not necessarily have the same handedness (hence they
may disagree on the clockwise direction).
We also show how the robots can detect termination, i.e., detect when the
Near-Gathering problem has been solved. This is crucial when the robots have to
perform a generic task after having nearly gathered. We show that termination
detection can be obtained even if the total number of robots is unknown to the
robots themselves (i.e., it is not a parameter of the algorithm), and robots
have no way to explicitly communicate.Comment: 25 pages, 8 fiugre
Gathering on Rings for Myopic Asynchronous Robots With Lights
We investigate gathering algorithms for asynchronous autonomous mobile robots moving in uniform ring-shaped networks. Different from most work using the Look-Compute-Move (LCM) model, we assume that robots have limited visibility and lights. That is, robots can observe nodes only within a certain fixed distance, and emit a color from a set of constant number of colors. We consider gathering algorithms depending on two parameters related to the initial configuration: M_{init}, which denotes the number of nodes between two border nodes, and O_{init}, which denotes the number of nodes hosting robots between two border nodes. In both cases, a border node is a node hosting one or more robots that cannot see other robots on at least one side. Our main contribution is to prove that, if M_{init} or O_{init} is odd, gathering is always feasible with three or four colors. The proposed algorithms do not require additional assumptions, such as knowledge of the number of robots, multiplicity detection capabilities, or the assumption of towerless initial configurations. These results demonstrate the power of lights to achieve gathering of robots with limited visibility
Meeting in a Polygon by Anonymous Oblivious Robots
The Meeting problem for searchers in a polygon (possibly with
holes) consists in making the searchers move within , according to a
distributed algorithm, in such a way that at least two of them eventually come
to see each other, regardless of their initial positions. The polygon is
initially unknown to the searchers, and its edges obstruct both movement and
vision. Depending on the shape of , we minimize the number of searchers
for which the Meeting problem is solvable. Specifically, if has a
rotational symmetry of order (where corresponds to no
rotational symmetry), we prove that searchers are sufficient, and
the bound is tight. Furthermore, we give an improved algorithm that optimally
solves the Meeting problem with searchers in all polygons whose
barycenter is not in a hole (which includes the polygons with no holes). Our
algorithms can be implemented in a variety of standard models of mobile robots
operating in Look-Compute-Move cycles. For instance, if the searchers have
memory but are anonymous, asynchronous, and have no agreement on a coordinate
system or a notion of clockwise direction, then our algorithms work even if the
initial memory contents of the searchers are arbitrary and possibly misleading.
Moreover, oblivious searchers can execute our algorithms as well, encoding
information by carefully positioning themselves within the polygon. This code
is computable with basic arithmetic operations, and each searcher can
geometrically construct its own destination point at each cycle using only a
compass. We stress that such memoryless searchers may be located anywhere in
the polygon when the execution begins, and hence the information they initially
encode is arbitrary. Our algorithms use a self-stabilizing map construction
subroutine which is of independent interest.Comment: 37 pages, 9 figure
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