Hierarchical Multi-Agent Navigation Through the 72-h Thermal Drift Cliff

Long-endurance unmanned aerial vehicle (UAV) missions beyond 72 consecutive flight hours face a reliability boundary at which thermal gyroscope drift drives the inertial navigation system (INS) position error into rapid nonlinear divergence at a predictable threshold tc. This paper presents BAZ II, a simulation-validated multi-agent navigation system that extends the analytical BAZ (bifurcation-aware zonal navigation) framework. Its central idea is to treat communication quality as a planning resource and combine it with multi-agent collaboration, making the navigation cliff a manageable degradation event rather than a hard operating limit. Four contributions support this idea: a thermalhysteresis MEMS gyroscope drift model reproduces the analytical cliff in simulation and supplies its physical mechanism; a distributed collaborative simultaneous localization and mapping (SLAM) filter coupled to a stochastic continuous-time Markov chain (CTMC) interagent channel sustains GPS-denied localization within the operational accuracy budget; a 3D Gaussian process RF-aware model predictive controller (MPC) with cognitive radio frequency-hopping restores link availability under jamming, while an analytic hierarchy process (AHP)-weighted multi-objective communication cost improves latency and jitter at negligible signal-to-noise ratio cost; finally, the integrated controller executes within the onboard real-time budget of an NVIDIA Jetson Xavier NX. All results are obtained in simulation, with hardware-in-the-loop and field testing remaining as priority future work.