Architecture
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Architecture in robotics and AI refers to the organizational framework that defines how a system's components — sensors, processors, planners, actuators, and software modules — are structured and interact to produce intelligent behavior. Rather than a single algorithm, an architecture is the blueprint governing information flow, decision-making hierarchies, and coordination across subsystems. In robotics, architectures range from hierarchical designs, where high-level planners command lower-level controllers in layered sequences, to reactive (behavior-based) systems that respond directly to sensory input without deliberate planning, to hybrid approaches combining both. Frameworks like ROS 2 provide standardized middleware architectures enabling modular, distributed robot software. In AI, architectural patterns include hierarchical mixture models, multi-agent coordination frameworks, and deep learning network designs such as YOLO for real-time perception. Architecture matters because it fundamentally determines a system's scalability, fault tolerance, real-time responsiveness, and ability to handle complexity. Poorly designed architectures create bottlenecks and brittleness; well-designed ones enable robots to navigate dynamic environments, coordinate in teams, and integrate perception with action reliably — making architecture a foundational concern for any capable autonomous system.
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