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arXiv · 2404.02111

Risk-Aware Real-Time Task Allocation for Stochastic Multi-Agent Systems under STL Specifications

Maico H. W. Engelaar·Zengjie Zhang·Eleftherios E. Vlahakis·Dimos V. Dimarogonas·Mircea Lazar·Sofie Haesaert
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Abstract

This paper addresses the control synthesis of heterogeneous stochastic linear multi-agent systems with real-time allocation of signal temporal logic (STL) specifications. Based on previous work, we decompose specifications into sub-specifications on the individual agent level. To leverage the efficiency of task allocation, a heuristic filter evaluates potential task allocation based on STL robustness, and subsequently, an auctioning algorithm determines the definitive allocation of specifications. Finally, a control strategy is synthesized for each agent-specification pair using tube-based model predictive control (MPC), ensuring provable probabilistic satisfaction. We demonstrate the efficacy of the proposed methods using a multi-shuttle scenario that highlights a promising extension to automated driving applications like vehicle routing.

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Maico H. W. Engelaar, Zengjie Zhang, Eleftherios E. Vlahakis, Dimos V. Dimarogonas, Mircea Lazar, Sofie Haesaert. 2024-04-02. Risk-Aware Real-Time Task Allocation for Stochastic Multi-Agent Systems under STL Specifications. https://arxiv.org/abs/2404.02111

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