Sensor fusion in a SMA-based hexapod bio-mimetic robot

摘要

This paper implement three different algorithms for sensor fusion in a shape memory alloy (SMA) based hexapod bio-mimetic robot; a Kalman filter minimizes the estimation error variance, an H <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</inf> filter minimizes the worst-case estimation error, and a robust mixed Kalman/H <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</inf> filter that takes care of the system uncertainty. The study installed a calibrated inertial measurement unit and an electric compass sensor on the robot for inertial guidance as well as step touch sensors to estimate legged odometry. The performances of the two-dimensional inertial navigation are then compared for evaluation.