A unified mathematical model for synchronisation and swarming has recently been proposed. Each system entity, called a "swarmalator", coordinates its internal phase and location with the other entities in a way that these two attributes are mutually coupled. This paper realises and studies, for the first time, the concept of swarmalators in a technical system. We adapt and extend the original model for its use with mobile robots and implement it in the Robot Operating System 2 (ROS 2). Simulations and experiments with small robots demonstrate the feasibility of the model and show its potential to be applied to real-world systems. All types of space-time patterns achieved in theory can be reproduced in practice. Applications can be found in monitoring, exploration, entertainment and art, among other domains.
Synchronisation is often applied in technology, e.g. for slotted communication or in robotic swarms to allocate and execute tasks together. One of the popular algorithms applied in those scenarios is firefly synchronisation because entities have to exchange only simple pulses. It can be used in wireless networks @cite_9 @cite_8 , but other, simpler communication interfaces can be used to emit and receive pulses as well (e.g. sound @cite_17 and light @cite_4 ).
@cite_9 @cite_4 @cite_17 @cite_8
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The convergence and precision of synchronization algorithms based on the theory of pulse-coupled oscillators is evaluated on programmable radios. Measurements in different wireless topologies show that such algorithms reach precisions in the low microsecond range. Based on the observation that phase rate deviation among radios is a limiting factor for the achievable precision, we propose a distributed algorithm for automatic phase rate equalization and show by experiments that an improved precision below one microsecond is possible in the given setups. It is also experimentally demonstrated that the stochastic nature of coupling is a key ingredient for convergence to synchrony. The proposed scheme can be applied in wireless systems for distributed synchronization of transmission slots, or sleep cycles. Recently, there has been growing interest in the synchronization of mobile pulse-coupled oscillators. We build on the work by (Phys. Rev. Lett. 110, 114101) and show that agents that interact exclusively with others in their cone of vision can exhibit different synchronization regimes. Depending on their speed, synchronization emerges as a slow process through spreading of the local coherence, as a fast process where global synchronization dominates, or it is inhibited for a range of intermediate speeds. In addition, we show that, not only the speed of the agents, but also their angle and range of interaction can tune the appearance of this intermediate regime. Self-organized synchronization is a common phenomenon observed in many natural and artificial systems: simple coupling rules at the level of the individual components of the system result in an overall coherent behavior. Owing to these properties, synchronization appears particularly interesting for swarm robotics systems, as it allows robust temporal coordination of the group while minimizing the complexity of the individual controllers. The goal of the experiments presented in this paper is the study of self-organizing synchronization for robots that present an individual periodic behavior. In order to design the robot controllers, we make use of artificial evolution, which proves to be capable of synthesizing minimal synchronization strategies based on the dynamical coupling between robots and environment. The obtained results are analyzed under a dynamical system perspective, which allows us to uncover the evolved mechanisms and to predict the scalability properties of the self-organizing synchronization with respect to varying group size. Synchronization is considered a particularly difficult task in wireless sensor networks due to its decentralized structure. Interestingly, synchrony has often been observed in networks of biological agents (e.g., synchronously flashing fireflies, or spiking of neurons). In this paper, we propose a bio-inspired network synchronization protocol for large scale sensor networks that emulates the simple strategies adopted by the biological agents. The strategy synchronizes pulsing devices that are led to emit their pulses periodically and simultaneously. The convergence to synchrony of our strategy follows from the theory of Mirollo and Strogatz, 1990, while the scalability is evident from the many examples existing in the natural world. When the nodes are within a single broadcast range, our key observation is that the dependence of the synchronization time on the number of nodes N is subject to a phase transition: for values of N beyond a specific threshold, the synchronization is nearly immediate; while for smaller N, the synchronization time decreases smoothly with respect to N. Interestingly, a tradeoff is observed between the total energy consumption and the time necessary to reach synchrony. We obtain an optimum operating point at the local minimum of the energy consumption curve that is associated to the phase transition phenomenon mentioned before. The proposed synchronization protocol is directly applied to the cooperative reach-back communications problem. The main advantages of the proposed method are its scalability and low complexity.