Using eventually consistent compasses to gather memory-less mobile robots with limited visibility
ACM Transactions on Autonomous and Adaptive Systems (TAAS)
A Self-stabilizing Marching Algorithm for a Group of Oblivious Robots
OPODIS '08 Proceedings of the 12th International Conference on Principles of Distributed Systems
Taking Advantage of Symmetries: Gathering of Asynchronous Oblivious Robots on a Ring
OPODIS '08 Proceedings of the 12th International Conference on Principles of Distributed Systems
Taking advantage of symmetries: Gathering of many asynchronous oblivious robots on a ring
Theoretical Computer Science
Pattern formation through optimum matching by oblivious CORDA robots
OPODIS'10 Proceedings of the 14th international conference on Principles of distributed systems
Proceedings of the twenty-third annual ACM-SIAM symposium on Discrete Algorithms
Convergence of mobile robots with uniformly-inaccurate sensors
SIROCCO'09 Proceedings of the 16th international conference on Structural Information and Communication Complexity
How simple robots benefit from looking back
CIAC'10 Proceedings of the 7th international conference on Algorithms and Complexity
The optimal tolerance of uniform observation error for mobile robot convergence
Theoretical Computer Science
The Gathering Problem for Two Oblivious Robots with Unreliable Compasses
SIAM Journal on Computing
How to meet asynchronously at polynomial cost
Proceedings of the 2013 ACM symposium on Principles of distributed computing
Deterministic polynomial approach in the plane
ICALP'13 Proceedings of the 40th international conference on Automata, Languages, and Programming - Volume Part II
Price of asynchrony in mobile agents computing
Theoretical Computer Science
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A number of recent studies concern algorithms for distributed control and coordination in systems of autonomous mobile robots. The common theoretical model adopted in these studies assumes that the positional input of the robots is obtained by perfectly accurate visual sensors, that robot movements are accurate, and that internal calculations performed by the robots on (real) coordinates are perfectly accurate as well. The current paper concentrates on the effect of weakening this rather strong set of assumptions and replacing it with the more realistic assumption that the robot sensors, movement, and internal calculations may have slight inaccuracies. Specifically, the paper concentrates on the ability of robot systems with inaccurate sensors, movements, and calculations to carry out the task of convergence. The paper presents several impossibility theorems, limiting the inaccuracy levels that still allow convergence, and prohibiting a general algorithm for gathering, namely, meeting at a point, in a finite number of steps. The main positive result is an algorithm for convergence under bounded measurement, movement, and calculation errors.