Neuro-symbolic framework for multi-USV coordination: COLREGs-compliant and energy-efficient smart navigation
TL;DR
NSC-Marine is proposed, a neuro-symbolic framework that conceptually addresses coupled constraints of coordinating multiple unmanned surface vehicles in coastal waters and combines multimodal causal perception, LLM-based rule reasoning, energy-aware motion planning, and distributed fault reconfiguration within a dual-rate control architecture.
Abstract
Coordinating multiple unmanned surface vehicles (USVs) in coastal waters requires simultaneous consideration of COLREGs compliance, real-time response, energy efficiency, fault tolerance, and semantic scene understanding. Existing approaches typically address only part of this problem and provide limited support for integrated fleet-level coordination. This paper proposes NSC-Marine, a neuro-symbolic framework that conceptually addresses these coupled constraints. It combines multimodal causal perception, LLM-based rule reasoning, energy-aware motion planning, and distributed fault reconfiguration within a dual-rate control architecture. To improve deployment safety, semantic reasoning is used to generate structured constraints, while low-level motion execution remains under deterministic planning and control. The framework is evaluated strictly within a physics-based simulation environment with approximately 70% overall fidelity, involving 1,000 trials of 20–100 USVs under Beaufort Scale 3–5 conditions. Under these simulated conditions, NSC-Marine achieves 88.7% ± 2.3% COLREGs compliance, 82.3% mission success under compound faults, and 13.6% energy reduction relative to the RLCA baseline, while maintaining a 320 ms critical-path latency. These metrics reflect an idealized simulation baseline and must not be generalized to physical deployment readiness. Real-world performance remains unvalidated, and staged hardware-in-the-loop testing and field trials are required to characterize the system’s actual behavior under physical disturbances.