Ansh Karnwal@ak605

RoboLens is a vision-guided coordination system designed to enable intelligent, system-level autonomy across fleets of autonomous robots. Traditional robotic systems rely heavily on onboard sensors, which limits awareness to local surroundings and often results in isolated decision-making. RoboLens addresses this limitation by introducing an overhead multi-camera infrastructure that functions as a centralized perception layer. These cameras continuously monitor the environment, detecting spills, fallen objects, human presence, congestion, and restricted zone violations in real time. Detections from multiple cameras are fused into a unified world model, providing a consistent and system-wide representation of the environment. An AI-driven reasoning engine evaluates event severity, spatial relationships, safety constraints, and robot availability to dynamically prioritize tasks. A centralized scheduler then assigns or reassigns robots in real time, ensuring efficient task distribution, conflict resolution, and congestion mitigation. By decoupling perception from individual robots and centralizing coordination, RoboLens transforms isolated robotic units into a cohesive, adaptive fleet. Its modular and hardware-agnostic architecture is designed to scale from simulation to real-world warehouse, manufacturing, hospital, and smart facility deployments.

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