Navigation & SLAM

Dead Reckoning

Dead Reckoning is the estimation of a robot's current pose by integrating motion measurements, such as wheel odometry, IMU readings, or commanded velocities, from a known starting point. Because each measurement carries noise and bias, integration causes the pose estimate to drift without bound over time. Practical systems therefore fuse dead reckoning with absolute corrections from GPS, visual landmarks, or map matching.

Why it matters for physical AI

Drift-prone odometry is the default state estimate whenever exteroceptive sensing drops out, so its error characteristics shape sensor fusion design. Understanding dead reckoning failure modes is essential for robust localization in warehouses, homes, and outdoor deployments.