#quantum machine learning #robotics

Modern robotic systems increasingly rely on learning-based perception, prediction, and decision making modules that must operate under strict constraints on latency, compute, energy, and reliability. In many robotic platforms (mobile robots, drones, autonomous vehicles, ...), inference must execute on embedded or edge hardware while remaining robust to sensor noise, distribution shifts, and safety-critical failures.