Optimal distributed interconnectivity of multi-robot systems by spatially-constrained clustering

Abstract

A spatially-constrained clustering algorithm is presented in this paper. This algorithm is a distributed clustering approach to fine-tune the optimal distances between agents of the system to strengthen the data passing among them using a set of spatial constraints. In fact, this method will increase interconnectivity among agents and clusters, leading to improvement of the overall communicative functionality of the multi-robot system. This strategy will lead to the establishment of loosely-coupled connections among the clusters. These implicit interconnections will mobilize the clusters to receive and transmit information within the multi-agent system. In other words, this algorithm classifies each agent into the clusters with the lowest cost of local communication with its peers. This research demonstrates that the presented decentralized method will actually boost the communicative agility of the swarm by probabilistic proof of the acquired optimality. Hence, the common assumption regarding the full-knowledge of the agents' primary locations has been fully relaxed compared to former methods. Consequently, the algorithm's reliability and efficiency is confirmed. Furthermore, the method's efficacy in passing information will improve the functionality of higher-level swarm operations, such as task assignment and swarm flocking. Analytical investigations and simulated accomplishments, corresponding to highlypopulated swarms, prove the claimed efficiency and coherence.

Self-organizing nest migration dynamics synthesis for ant colony systems

“…In other words, passivity of a self-organizing system may be exploited to activate its various behavioral modes instead of designing complex controllers to make the system exhibit those behaviors. These generalizations may indeed provide insights to establish more versatile ant-colony-based algorithms to be of service to many applications of self-organization such as, multi-robot systems [10], wireless sensor networks [11], and so forth.…”

“…To be specific, the existence of a spatial equilibrium entails that, given a fixed time slot, the pheromone dynamics all over the pathway graph are stationary. So, considering and taking (10) into account, we finally yield…”

Fixed-Time Formation Control of Multirobot Systems: Design and Experiments

“…Under this background, distributed cooperative control strategies including consensus control and formation control, have attracted lots of attention and have been studied intensively in the literature, [3]- [14], to mention a few. By using distributed clustering approach, the overall computational workload in a multi-robot systems can be probabilistically reduced [15]. Furthermore, event-triggered mechanism can also be used in distributed cooperative control to reduces the unnecessary information exchange between the robots [16], [17].…”

Efficient Resource Distribution by Adaptive Inter-agent Spacing in Multi-agent Systems

“…A distributed gradual pattern formation algorithm based on the Turing diffusion-driven instability theory was proposed in [18]. Mactoobian et al showed that the overall computational workload in a multi-agent system can be probabilistically reduced by a distributed clustering approach [19]. Unnecessary information exchange between agents can also be minimized by event-triggered mechanisms in distributed cooperative control [20], [21].…”