Intelligence for the physical world.

Localization is fundamental to intelligent physical systems. Yet many environments cannot rely on GPS, surveyed anchors, precise ranging or dense infrastructure.

Our research investigates new methods for determining the relative position of wireless devices using limited information such as connectivity, communication relationships, transmission power and environmental structure.

A major focus is anchor-free and range-free localization. Instead of asking devices to measure exact distances from known reference points, these methods infer spatial structure from the way devices interact with one another.

Artificial intelligence is moving beyond purely digital environments.

Physical AI brings intelligence into machines, sensors, infrastructure and connected objects operating in the real world.

Rather than depending entirely on centralized cloud intelligence, future systems should increasingly understand and respond to conditions locally. The physical environment becomes part of the intelligence.

Many of the most important opportunities for sensing, AI and connectivity exist outside traditional digital environments.

Factories, mines, construction sites, logistics networks and infrastructure generate enormous physical complexity. Our research explores technologies designed specifically for these environments.

A core principle is that industrial technology must work under real operational constraints, including physical durability, unreliable connectivity, limited power, changing environments, scale, safety and operational practicality.