Gathering with extremely restricted visibility

We consider the classical problem of making mobile processes gather or converge at a same position (as performed by swarms of animals in Nature). Existing works assume that each process can see all other processes, or all processes within a certain radius. In this paper, we introduce a new model with an extremely restricted visibility: each process can only see one other process (its closest neighbor). Our goal is to see if (and to what extent) the gathering and convergence problems can be solved in this setting. We first show that, surprisingly, the problem can be solved for a small number of processes (at most 5), but not beyond. This is due to indeterminacy in the case where there are several closest neighbors for a same process. By removing this indeterminacy with an additional hypothesis (choosing the closest neighbor according to an order on the positions of processes), we then show that the problem can be solved for any number of processes. We also show that up to one crash failure can be tolerated for the convergence problem.

[1]  Reuven Cohen,et al.  Robot Convergence via Center-of-Gravity Algorithms , 2004, SIROCCO.

[2]  M. Nice,et al.  Bird flocks and the breeding cycle : a contribution to the study of avian sociality , 1938 .

[3]  Masafumi Yamashita,et al.  Distributed memoryless point convergence algorithm for mobile robots with limited visibility , 1999, IEEE Trans. Robotics Autom..

[4]  Mark Cieliebak,et al.  Gathering Autonomous Mobile Robots , 2002, SIROCCO.

[5]  M Dorigo,et al.  Ant colonies for the travelling salesman problem. , 1997, Bio Systems.

[6]  山内 由紀子,et al.  Plane Formation by Synchronous Mobile Robots in the Three-Dimensional Euclidean Space , 2019 .

[7]  Roberto Montemanni,et al.  Design patterns from biology for distributed computing , 2006, TAAS.

[8]  Masafumi Yamashita,et al.  Formation and agreement problems for synchronous mobile robots with limited visibility , 1995, Proceedings of Tenth International Symposium on Intelligent Control.

[9]  Noa Agmon,et al.  Fault-tolerant gathering algorithms for autonomous mobile robots , 2004, SODA '04.

[10]  Masafumi Yamashita,et al.  Distributed Anonymous Mobile Robots: Formation of Geometric Patterns , 1999, SIAM J. Comput..

[11]  Nicola Santoro,et al.  Gathering of asynchronous robots with limited visibility , 2005, Theor. Comput. Sci..

[12]  Friedhelm Meyer auf der Heide,et al.  The Impact of the Gabriel Subgraph of the Visibility Graph on the Gathering of Mobile Autonomous Robots , 2016, ALGOSENSORS.

[13]  Ichiro Suzuki,et al.  Distributed algorithms for formation of geometric patterns with many mobile robots , 1996, J. Field Robotics.

[14]  R. Millar,et al.  Detection of spatial variability in relative density of fishes: comparison of visual census, angling, and baited underwater video , 2000 .

[15]  Nicola Santoro,et al.  Solving the Robots Gathering Problem , 2003, ICALP.

[16]  Noga Alon,et al.  A Biological Solution to a Fundamental Distributed Computing Problem , 2011, Science.