1901: Charles Stark Draper is born

On 2 October 1901, Charles Stark Draper was born in Windsor, Missouri. Trained first in psychology and then in engineering at Stanford and MIT, he devoted his career to the problem of knowing where you are and which way you are pointing when no external landmarks are available. He became the acknowledged father of inertial navigation — the art of using gyroscopes and accelerometers to track motion through pure calculation.

At MIT he founded the Instrumentation Laboratory, a unique institution that brought physicists, engineers and early computer scientists together. During the Second World War the lab produced advanced fire-control systems; afterwards it turned to ballistic-missile guidance and, most famously, to the navigation systems of the Apollo spacecraft.

The Apollo Guidance Computer that Draper’s team created was a landmark in computing history. It was one of the earliest machines to rely heavily on integrated circuits, operated under severe real-time constraints, and had to be trusted with human lives a quarter of a million miles from Earth. Its software introduced priority-based multitasking and rigorous development methods that still echo in safety-critical AI systems.

The intellectual thread that runs from Draper to contemporary artificial intelligence is the problem of state estimation. Inertial systems must fuse noisy, high-frequency sensor data into a coherent picture of position and orientation — precisely the challenge faced by today’s robots, autonomous vehicles and drones. Techniques refined in his laboratory, including early digital implementations of Kalman filtering, became foundational tools in probabilistic robotics and sensor fusion, core components of modern machine-learning pipelines for perception and control.

Today Draper’s legacy is everywhere: in the tiny inertial sensors inside every smartphone, in the navigation stacks of self-driving cars, and in the guidance computers of planetary rovers. The seamless integration of physical sensing and on-board intelligence that he championed remains essential to embodied AI. On this day we remember the engineer who taught machines how to know where they are — a prerequisite for any artificial agent that hopes to act in the world.