The OpenCV AI Kit (OAK) is an innovative platform designed for spatial AI applications. It incorporates advanced features such as real-time object detection, depth sensing, and visual tracking, allowing AI models to better understand and interact with their environments. This hardware-accelerated solution includes a powerful camera system that supports machine learning capabilities, enabling a wide range of applications from robotics to smart surveillance and beyond.

The Multi Agent Robotic System project offers a modular Python-based platform for developing, simulating, and deploying cooperative robotic teams. At its core, it implements decentralized control strategies, enabling robots to share state information and collaboratively allocate tasks without a central coordinator. The system includes built-in modules for path planning, collision avoidance, environment mapping, and dynamic task scheduling. Developers can integrate new algorithms by extending provided interfaces, adjust communication protocols via configuration files, and visualize robot interactions in simulated environments. Compatible with ROS, it supports seamless transitions from simulation to real-world hardware deployments. This framework accelerates research by providing reusable components for swarm behavior, collaborative exploration, and warehouse automation experiments.