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In this paper, we propose a distributed control policy to achieve rendezvous by a set of robots even when some robots in the system do not follow the prescribed policy. These nonconforming robots correspond to faults in the multirobot system, and our control policy is thus a fault-tolerant policy. Each robot has a limited sensing range and is able to directly estimate the state of only those robots within that sensing range, which induces a network topology for the multirobot system. We assume that it is not possible for the fault-free robots to identify the faulty robots, and thus our approach is robust even to undetected faults in the system. The main contribution of this paper is a fault-tolerant distributed control algorithm that is guaranteed to converge to consensus under certain reasonable connectivity conditions. We first present a general algorithm that exploits the notion of a Tverberg partition of a point set in R d , and give a proof of convergence. We then provide three instantiations of this algorithm, based on three different sensing models. For each case, we analyze performance via extensive simulations. The effectiveness and performance of our algorithms on real platforms are demonstrated through experiments on a multirobot testbed.
Park et al. (Wed,) studied this question.