The project aims to develop a foundational architecture for immersive and robotic systems, focusing on distributed real-time data capture, low-latency decentralized computation, and dynamic multimodal output generation. The architecture will support collaborative AR/VR environments, human-robot teaming, and ambient computing networks. Key features include ultra-low latency, low power design, and a hardware-agnostic input layer that accepts data from various sources such as sensors, wearables, and edge cameras. The modular compute layer will perform logic, physics, and agent-based reasoning on distributed nodes, while the flexible output layer will generate spatial data, 3D geometry, synthesized video, or action commands. The system will also incorporate AI-enhanced configuration using LLMs and orchestrator agents to dynamically assign tasks and balance loads. Use of existing computing architecture like the Robotic Operating System (ROS) will be explored and considered

The project will deliver a core system design with low-level APIs for data capture, compute coordination, and output delivery. Two working prototypes will be developed: one for AR environment collaboration and another for human-robot sensor/actuator co-processing. An agent orchestration layer using lightweight LLMs will be created for dynamic configuration. Additionally, latency and power benchmarks will be conducted on mobile and embedded hardware, and comprehensive documentation and a modular SDK will be provided to support future integration in various applications.