You are provided with the abstract of a scientific paper and the abstracts of the papers it references. Your task is to write a Related Work section for the main paper. This section should concisely summarize and integrate the key points from the cited abstracts, reflecting how they relate to the main paper's contributions and context. In your summary, use numerical citation markers like [1], [2], etc., to refer to the corresponding papers.

Main Abstract:
The Meeting problem for @math searchers in a polygon @math (possibly with holes) consists in making the searchers move within @math , 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 @math , we minimize the number of searchers @math for which the Meeting problem is solvable. Specifically, if @math has a rotational symmetry of order @math (where @math corresponds to no rotational symmetry), we prove that @math searchers are sufficient, and the bound is tight. Furthermore, we give an improved algorithm that optimally solves the Meeting problem with @math 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.

Cited Abstract(s):
[1]: In this paper we study the problem of gathering a collection of identical oblivious mobile robots in the same location of the plane. Previous investigations have focused mostly on the unlimited visibility setting, where each robot can always see all the others regardless of their distance.In the more difficult and realistic setting where the robots have limited visibility, the existing algorithmic results are only for convergence (towards a common point, without ever reaching it) and only for semi-synchronous environments, where robots' movements are assumed to be performed instantaneously.In contrast, we study this problem in a totally asynchronous setting, where robots' actions, computations, and movements require a finite but otherwise unpredictable amount of time. We present a protocol that allows anonymous oblivious robots with limited visibility to gather in the same location in finite time, provided they have orientation (i.e., agreement on a coordinate system).Our result indicates that, with respect to gathering, orientation is at least as powerful as instantaneous movements.

[2]: We present a distributed algorithm for converging autonomous mobile robots with limited visibility toward a single point. Each robot is an omnidirectional mobile processor that repeatedly: 1) observes the relative positions of those robots that are visible; 2) computes its new position based on the observation using the given algorithm; 3) moves to that position. The robots' visibility is limited so that two robots can see each other if and only if they are within distance V of each other and there are no other robots between them. Our algorithm is memoryless in the sense that the next position of a robot is determined entirely from the positions of the robots that it can see at that moment. The correctness of the algorithm is proved formally under an abstract model of the robot system in which: 1) each robot is represented by a point that does not obstruct the view of other robots; 2) the robots' motion is instantaneous; 3) there are no sensor and control error; 4) the issue of collision is ignored. The results of computer simulation under a more realistic model give convincing indication that the algorithm, if implemented on physical robots, will be robust against sensor and control error.
The case of limited visibility has been studied, as well. Any given pattern can be formed by asynchronous robots with agreement on a coordinate system [1] . Without such agreement, it is still possible to converge to the same point, perhaps without ever reaching it [2] .