Simultaneous Calibration of a Hexapod Robot and an IMU Sensor Model Based on Raw Measurements

Abstract

A simulation model contributes to the development of both algorithms based on navigation sensors and their application in real nonlinear mechatronic systems. The Szabad(ka)-II hexapod walker robot is equipped with an inertial measurement unit (IMU), and this paper presents a novel calibration procedure of its simulation model. Various sinusoidal calibration movements were performed on both the model and the robot, and the raw IMU measurements were recorded simultaneously with motor electrical parameters and joint movement variables. The simulation model includes the model of IMU sensors, where the location, misalignments, and scaling parameters are also incorporated in the tuning procedure. Thus, this simulation environment enabled the calibration procedure to be performed based on the measurement data. The efficient optimization of both the unknown and estimated parameters of the robot model along with the IMU sensor model resulted in a simulation output that fits the measurement results satisfactorily. The nominal and remaining errors were analyzed both statistically and in the spectral domain. Due to the proposed method, the simulation error of the accelerometer and gyroscope measurements were decreased by 35%. The necessity of calibrating the sensor model was justified via the application of an extended Kalman filter (EKF) for the attitude estimation.