Control of Multi-agent Systems under STL Specifications based on Prescribed Performance Observers

Researchers at KTH Royal Institute of Technology (Zaccherini, Liu, Dimarogonas) have introduced a novel decentralized control framework for large-scale heterogeneous multi-agent systems. The work, published on arXiv (2604.22315), addresses a critical challenge in robotics: how to coordinate swarms of diverse agents (e.g., drones, ground robots) on complex spatiotemporal tasks—formalized as Signal Temporal Logic (STL) specifications—when each agent can only communicate with its immediate neighbors. The specifications require collaboration among agents that may be several communication hops apart.

The core innovation is a k-hop Prescribed Performance State Observer (k-hop PPSO). This observer enables each agent to estimate the states of agents up to k communication hops away using only information from its 1-hop neighbors. Crucially, it provides predefined performance bounds on the estimation errors. The researchers then explicitly incorporate these error bounds into a reformulation of the spatial robustness of the STL specifications, yielding worst-case robustness measures that account for estimation uncertainty. Based on this modified robustness, a decentralized continuous-time feedback control law guarantees that the multi-agent system satisfies the STL specifications, even under bounded external disturbances and estimation errors. The framework provides formal correctness guarantees using only local information and limited communication, with numerical simulations validating the results. This work builds on prior research (arXiv:2602.05586) and represents a significant step toward practical, scalable multi-robot coordination in communication-constrained environments.