7 research outputs found
Asynchronous Gathering of Robots with Finite Memory on a Circle under Limited Visibility
Consider a set of mobile entities, called robots, located and operating
on a continuous circle, i.e., all robots are initially in distinct locations on
a circle. The \textit{gathering} problem asks to design a distributed algorithm
that allows the robots to assemble at a point on the circle. Robots are
anonymous, identical, and homogeneous. Robots operate in a deterministic
Look-Compute-Move cycle within the circular path. Robots agree on the clockwise
direction. The robot's movement is rigid and they have limited visibility
, i.e., each robot can only see the points of the circle which is at an
angular distance strictly less than from the robot.
Di Luna \textit{et al}. [DISC'2020] provided a deterministic gathering
algorithm of oblivious and silent robots on a circle in semi-synchronous
(\textsc{SSync}) scheduler. Buchin \textit{et al}. [IPDPS(W)'2021] showed that,
under full visibility, robot model with \textsc{SSync}
scheduler is incomparable to robot (robots are silent but have
finite persistent memory) model with asynchronous (\textsc{ASync}) scheduler.
Under limited visibility, this comparison is still unanswered. So, this work
extends the work of Di Luna \textit{et al}. [DISC'2020] under \textsc{ASync}
scheduler for robot model
Rendezvous on a Known Dynamic Point on a Finite Unoriented Grid
In this paper, we have considered two fully synchronous
robots having no agreement on coordinates entering a finite unoriented grid
through a door vertex at a corner, one by one. There is a resource that can
move around the grid synchronously with the robots until it gets co-located
along with at least one robot. Assuming the robots can see and identify the
resource, we consider the problem where the robots must meet at the location of
this dynamic resource within finite rounds. We name this problem "Rendezvous on
a Known Dynamic Point".
Here, we have provided an algorithm for the two robots to gather at the
location of the dynamic resource. We have also provided a lower bound on time
for this problem and showed that with certain assumption on the waiting time of
the resource on a single vertex, the algorithm provided is time optimal. We
have also shown that it is impossible to solve this problem if the scheduler
considered is semi-synchronous
Space and move-optimal Arbitrary Pattern Formation on infinite rectangular grid by Oblivious Robot Swarm
Arbitrary Pattern Formation (APF) is a fundamental coordination problem in
swarm robotics. It requires a set of autonomous robots (mobile computing units)
to form any arbitrary pattern (given as input) starting from any initial
pattern. The APF problem is well-studied in both continuous and discrete
settings. This work concerns the discrete version of the problem. A set of
robots is placed on the nodes of an infinite rectangular grid graph embedded in
a euclidean plane. The movements of the robots are restricted to one of the
four neighboring grid nodes from its current position. The robots are
autonomous, anonymous, identical, and homogeneous, and operate
Look-Compute-Move cycles. Here we have considered the classical
robot model, i.e., the robots have no persistent memory and
no explicit means of communication. The robots have full unobstructed
visibility. This work proposes an algorithm that solves the APF problem in a
fully asynchronous scheduler under this setting assuming the initial
configuration is asymmetric. The considered performance measures of the
algorithm are space and number of moves required for the robots. The algorithm
is asymptotically move-optimal. A definition of the space-complexity is
presented here. We observe an obvious lower bound of the space
complexity and show that the proposed algorithm has the space complexity
. On comparing with previous related works, we show that this is
the first proposed algorithm considering robot model that is
asymptotically move-optimal and has the least space complexity which is almost
optimal
Circle Formation by Asynchronous Opaque Fat Robots on an Infinite Grid
This study addresses the problem of "Circle Formation on an Infinite Grid by
Fat Robots" (). Unlike prior work focused solely on point robots
in discrete domain, it introduces fat robots to circle formation on an infinite
grid, aligning with practicality as even small robots inherently possess
dimensions. The algorithm, named , resolves the
problem using a swarm of fat luminous robots. Operating under an asynchronous
scheduler, it achieves this with five distinct colors and by leveraging
one-axis agreement among the robots
Move and Time Optimal Arbitrary Pattern Formation by Asynchronous Robots on Infinite Grid
The \textsc{Arbitrary Pattern Formation} (\textsc{Apf}) is a widely studied
in distributed computing for swarm robots. This problem asks to design a
distributed algorithm that allows a team of identical, autonomous mobile robots
to form any arbitrary pattern given as input. This paper considers that the
robots are operating on a two-dimensional infinite grid. Robots are initially
positioned on distinct grid points forming an asymmetric configuration (no two
robots have the same snapshot). They operate under a fully asynchronous
scheduler and do not have any access to a global coordinate system, but they
will align the axes of their local coordinate systems along the grid lines. The
previous work dealing with \textsc{Apf} problem solved it in
robot movements under similar conditions, where
is the side of the smallest square that can contain both initial
and target configuration and, is the number of robots. Let
. This paper presents two algorithms of
\textsc{Apf} on an infinite grid. The first algorithm solves the \textsc{Apf}
problem using asymptotically move optimal. The second
algorithm solves the \textsc{Apf} problem in epochs, which we
show is asymptotically optimal
Time Optimal Gathering of Robots on an Infinite Triangular Grid with Limited Visibility
This work deals with the problem of gathering of oblivious mobile
entities, called robots, with limited visibility, at a point (not known
beforehand) placed on an infinite triangular grid. Earlier works of gathering
mostly considered the robots either on a plane or on a circle or on a
rectangular grid under both full and limited visibility. In the triangular
grid, there are two works to the best of our knowledge. The first one is
arbitrary pattern formation where full visibility is considered (\cite{C21}).
The other one considers seven robots with 2- hop visibility that form a hexagon
with one robot in the center of the hexagon in a collision-less environment
under a fully synchronous scheduler (\cite{ShibataOS00K21}).
In this work, we first show that gathering on a triangular grid with 1-hop
vision of robots is not possible even under a fully synchronous scheduler if
the robots do not agree on any axis. So one axis agreement has been considered
in this work (i.e., the robots agree on a direction and its orientation). We
have also showed that the lower bound for time is epochs when
number of robots are gathering on an infinite triangular grid. An algorithm is
then presented where a swarm of number of robots with 1-hop visibility can
gather within epochs under a semi-synchronous scheduler. So the
algorithm presented here is time optimal
Arbitrary pattern formation by asynchronous opaque robots on infinite grid
Arbitrary pattern formation () by mobile robots is studied by
many in literature under different conditions and environment. Recently it has
been studied on an infinite grid network but with full visibility. In opaque
robot model, circle formation on infinite grid has also been studied. In this
paper, we are solving on infinite grid with asynchronous opaque
robots with lights. The robots do not share any global co-ordinate system. The
main challenge in this problem is to elect a leader to agree upon a global
co-ordinate where the vision of the robots are obstructed by other robots.
Since the robots are on a grid, their movements are also restricted to avoid
collisions. In this paper, the aforementioned hardness are overcome to produce
an algorithm that solves the problem