Distributed Anonymous Mobile Robots: Formation of Geometric Patterns
SIAM Journal on Computing
ICTCS '01 Proceedings of the 7th Italian Conference on Theoretical Computer Science
Gathering of asynchronous robots with limited visibility
Theoretical Computer Science
Self-deployment of mobile sensors on a ring
Theoretical Computer Science
Using eventually consistent compasses to gather memory-less mobile robots with limited visibility
ACM Transactions on Autonomous and Adaptive Systems (TAAS)
Uniform scattering of autonomous mobile robots in a grid
IPDPS '09 Proceedings of the 2009 IEEE International Symposium on Parallel&Distributed Processing
The cost of probabilistic agreement in oblivious robot networks
Information Processing Letters
Optimal Byzantine-resilient convergence in uni-dimensional robot networks
Theoretical Computer Science
Optimal and competitive runtime bounds for continuous, local gathering of mobile robots
Proceedings of the twenty-fourth annual ACM symposium on Parallelism in algorithms and architectures
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The scattering problem is a fundamental task for mobile robots, which requires that no two robots share the same position. We investigate the scattering problem in the limited-visibility model. In particular, we focus on connectivity-preservation property. That is, the scattering must be achieved so that the disconnection of the visibility graph never occurs (in the visibility graph robots are the nodes of the graph and the edges are their visibility relationship). The algorithm we propose assumes ATOM (i.e. semi-synchronous) model. In these settings our algorithm guarantees the connectivity-preserving property, and reaches a scattered configuration within O(min{n, D2 + log n}) asynchronous rounds in expectation, where D is the diameter of the initial visibility graph. Note that the complexity analysis is adaptive since it depends on D. This implies that our algorithm quickly scatters all robots crowded in a small-diameter visibility graph. We also provide a lower bound of Ω(n) for connectivity-preserving scattering. It follows that our algorithm is optimal in the sense of the non-adaptive analysis.