mlsanityData to 14 Oct 2026

Sensor-Driven Mission Synthesis for UAV/UGV Swarms: A TB-CSPN Coordination Architecture with Hardware-Enforced Safety

arXiv 2608.14306 ↗First posted 14 Aug 2026cs.AI cs.SY eess.SYcited by 0

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Abstract (arXiv)

This paper presents a coordination architecture for heterogeneous UAV/UGV swarms that synthesises mission actions from uncertain, multi-modal sensor evidence while preserving hardware-enforced safety at the actuation boundary. The approach combines radar, RF, acoustic, and visual observations with Topic-Based Communication Space Petri Net (TB-CSPN) orchestration to support incremental mission formation under partial and evolving information. Consultant agents transform sensor outputs into temporally bounded semantic tokens, while supervisor agents provide authorisation and policy-governed release of mission transitions. This separation between interpretation, coordination, and execution yields auditable decision paths, constrains non-determinism within the coordination layer through guards and synchronisation, and enables bounded-time integration of heterogeneous evidence. To improve resilience in contested environments, including cyber compromise, spoofing, jamming, and communication loss, the digital coordination layer is complemented by independent analogue safety envelopes that clamp or veto unsafe actuator commands issued to individual vehicles. A coastal-surveillance case study illustrates how the proposed architecture enables dependable, governed, and physically safe swarm coordination under operational uncertainty.

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References · 9

  1. 2022Multi-modal Sensor Fusion for Auto Driving Perception: A Surveycited by 76
  2. 2025Human-Artificial Interaction in the Age of Agentic AI: A System-Theoretical Approachcited by 22
  3. 2019Micro Air Vehicle Link (MAVLink) in a Nutshell: A Surveycited by 7
  4. 2020An Extensive Survey on the Internet of Dronescited by 4
  5. 2023Multi-UAV Adaptive Path Planning Using Deep Reinforcement Learningcited by 4
  6. 2024The Use of Artificial Intelligence in Military Intelligence: An Experimental Investigation of Added Value in the Analysis Processcited by 3
  7. 2025Electronic Warfare Cyberattacks, Countermeasures and Modern Defensive Strategies of UAV Avionics: A Surveycited by 3
  8. 2021Defense Against Adversarial Swarms with Parameter Uncertaintycited by 2
  9. 2023Aerial Swarm Defense using Interception and Herding Strategiescited by 1

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