Phase Stability Regulator Enhances Predictability for Autonomous Mobile Robots
A new phase stability regulator has been introduced to improve the predictability and stability of autonomous mobile robots (AMRs). This regulator addresses the computational challenges faced by AMRs in dynamic environments such as warehouses and hospitals. The system uses two dynamic parameters: an external task gradient (ΔN) and internal behavioral divergence (ΔD), to manage computational instability. By monitoring both environmental complexity and controller stability, the regulator aims to prevent computational overload, ensuring that AMRs can operate effectively without freezing or oscillating between behaviors. 
