Gathering Autonomous Mobile Robots Under the Adversarial Defected View Model
This work is significant for researchers in swarm robotics and distributed systems, as it provides solutions for robust robot gathering under challenging adversarial sensing conditions, resolving previously open cases.
This paper addresses the problem of gathering N autonomous mobile robots in a Euclidean plane under adversarial visibility faults, where robots may only observe a restricted subset of other robots. The authors present two distributed algorithms that achieve finite-time gathering: one for the fully synchronous model under (4, 2) defected view, and another for the asynchronous model under the general (N, K) defected view.
This paper studies the gathering problem for a set of $N \ge 2$ autonomous mobile robots operating in the Euclidean plane under the distributed Look-Compute-Move model. We consider oblivious robots executing under the adversarial defected view model, in which an activated robot may observe only a restricted subset of robots due to adversarial visibility faults. Consequently, the information obtained during each Look phase may be incomplete and dynamically altered. The objective is to guarantee deterministic finite-time gathering at a location not known a priori despite such sensing restrictions. We present two distributed algorithms under distinct scheduling assumptions. In the fully synchronous (FSYNC) model, we prove finite-time gathering in the adversarial (4, 2) defected view setting, resolving a previously open case without requiring additional capabilities or coordinate agreement. In the asynchronous (ASYNC) model, we establish finite-time gathering under the general adversarial (N, K) defected view model, where an activated robot observes at most K of the other $N - 1$ robots for any $1 \le K < N - 1$. Both results hold under non-rigid motion. The proposed algorithm for the ASYNC model assumes agreement in the direction and orientation of one coordinate axis.