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As cyber–physical networks become increasingly equipped with embedded capabilities, they are made vulnerable to malicious attacks with the increased number of access points available to attackers. A particularly pernicious attack is spoofing, in which a malicious agent spawns multiple identities and can compromise otherwise attack–resilient algorithms that rely on assumed network robustness structures. We generalize a class of resilient consensus strategies, known as weighted mean-subsequence-reduced (W-MSR) consensus, to further provide spoof resilience by incorporating a physical layer authentication. By comparing the physical fingerprints of received signals, legitimate agents can identify and isolate malicious agents that attempt spoofing attacks. A key technical contribution is to quantify worst case misclassification probability using distributionally robust Chebyshev bounds computed via semidefinite programming when the physical fingerprints of received signals are stochastic. Numerical simulations and experimental results illustrate the effectiveness of the proposed methods. Our framework is applicable to a variety of problems involving multirobot systems coordinating via wireless communication. [ABSTRACT FROM AUTHOR]

In this article, we present a distributed formation control strategy for agents with a variety of dynamics to achieve a desired planar formation. Our approach is based on the barycentric-coordinate-based (BCB) control, which is fully distributed, does not require interagent communication or a common sense of orientation, and can be implemented using relative position measurements acquired by agents in their local coordinate frames. This removes the need for global positioning or alignment of local coordinate frames, which are required across several existing strategies. We show how the BCB control for agents with the simplest dynamical model, i.e., the single-integrator dynamics, can be extended to agents with higher order dynamics such as quadrotors, and nonholonomic agents such as unicycles and cars. Specifically, our extension preserves the desired convergence and robustness guarantees of the BCB approach and is provably robust to saturations in the input and unmodeled linear actuator dynamics for unicycle and car agents. We further show that under our proposed BCB control design, the agents can move along a rotated and scaled control direction without affecting the convergence to the desired formation. This observation is used to design a fully distributed collision avoidance strategy, which is often not considered in the formation control literature. We demonstrate the proposed approach in simulations and further present a distributed robotic platform to test the strategy experimentally. Our experimental platform consists of off-the-shelf equipment that can be used to test and validate other multiagent algorithms. The code and implementation instructions for this platform are available online. [ABSTRACT FROM AUTHOR]