Accurate positioning will be central to AI agents and robots coexisting efficiently with humans in the smart cities of the future. Current GPS-based positioning systems are inadequate for AI agents and robots, particularly in dense urban environments, due to accuracy limitations, vulnerability to interference, and reliance on centralized infrastructure.

The Future of Positioning

In a wide-ranging presentation from AWE last year, Nils Pihl, the CEO of our member project Auki Labs, discusses how decentralized AI perception and collaborative spatial computing address the limitations of GPS, particularly in dense urban and indoor environments.

GPS struggles with accuracy in urban and indoor spaces due to signal obstructions from buildings and other infrastructure. This limitation makes it unreliable for precise positioning in retail settings, where accurate location data is critical for inventory management, in-store navigation, and automation. Traditional GPS also lacks the granularity required for effective augmented reality (AR) experiences and AI-driven spatial awareness.

The Auki network, Auki Labs’ decentralized spatial computing network or posemesh, enhances positioning by enabling devices to share real-time perception data without relying on centralized infrastructure. This improvement allows AI to navigate and interact within physical retail spaces with far greater accuracy than GPS. Unlike GPS, which provides only a static position, the Auki network offers real-time contextual awareness, helping AI understand movement, object placement, and environmental changes dynamically.

Challenging Urban & Indoor Environments

In retail, this advancement benefits autonomous robots, smart inventory tracking, and AR-assisted shopping experiences. For example, AI-powered systems can navigate store layouts with centimeter-level accuracy, reducing inefficiencies in stock management and checkout processes. Employees and customers can also use AR-enhanced applications to locate products more easily, improving overall shopping experiences.

Moreover, the decentralized nature of the posemesh means that AI can function effectively without depending on external cloud-based processing. This increases privacy, reduces latency, and allows seamless real-time interaction between AI agents and humans within retail spaces.

By overcoming GPS’s limitations, the posemesh significantly enhances AI-driven automation and efficiency in retail, laying the foundation for smarter, more responsive shopping environments.

Intercognitive Pillars

Nils’ presentation is particularly interesting in the context of our fifth pillar: positioning. There is a need for decentralized positioning systems (DPS) to support AI agents and robots in smart cities. The Auki network from Auki Labs represents the future of positioning by providing a decentralized, real-time spatial computing network that enables AI agents, robots, and devices to share precise spatial data dynamically. By fostering seamless collaboration between AI systems, Auki Labs paves the way for smarter navigation, automation, and spatial awareness across industries.

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