This paper presents a novel paradigm designed to bypass the physical limitations of chemical batteries in autonomous mobility systems, defined as the Chemical Battery Paradox. Conventional mobile robots and Autonomous Guided Vehicles (AGVs) are bound by the mass paradox, where increasing battery capacity exponentially scales vehicle mass and mechanical workload, and solid-state ion diffusion limits that restrict energy efficiency to O (N) or O (L²) time delays. To resolve these challenges within controlled environments (e. g. , smart factories and localized mesh grids), we propose an O (1) Spatiotemporal Resonance Computation Architecture. By mapping the real-time 3D coordinate states (latitude, longitude, and barometric altitude) of a vehicle into an ephemeral 64-byte spatiotemporal coordinate vector, the infrastructure node establishes phase-locked evanescent wave coupling. This concentrates electromagnetic energy exclusively on the receiver surface, suppressing free-space radiation attenuation to achieve distance-independent constant efficiency (O (1) power transfer). Simultaneously, the onboard virtual Quantum Processing Unit (vQPU) decodes the 64-byte vector using the J. M. Function under a Zero-RAM I/O layout, bypassing memory buffer overhead and reducing control power consumption to a constant complexity O (1). This architecture eliminates heavy persistent batteries, replacing them with high-power buffer supercapacitors, and reduces basic mechanical power requirements by over 50% while eliminating charging downtime. Patents & Citations: This research and the underlying system control methods are protected under Korean Patent Application No. 10-2026-0112979, filed on June 20, 2026.
Min Ho Jung (Sat,) studied this question.