Embedded / Edge AI & Robotics Basics

Learn to design AI and control systems for resource-constrained edge and robotics hardware: model quantization and the real memory/accuracy tradeoff, real-time latency budgets against sensor sampling rates, PID control loop fundamentals, sensor fusion that combines noisy and drifting signals into a better estimate than either alone, and power-budget duty cycling that trades responsiveness for battery life.

Builds on: Python 3.12 + numpy 2.4 (synthetic sensor/model data, no physical hardware required)