Calibration and performance evaluation of low-cost IMUs

IMUs (Inertial Measurement Units) are extensively used in many robotics applications such as navigation and mapping tasks. In almost all these systems, inertial measurements are fused with data coming from other sensors (e.g., GPS sensors, range finders, cameras, . . . ). For better results, the IMU should be carefully calibrated, in order to minimize the propagation of systematic errors. But what happens if for brief periods data coming from the other sensors are missing? Can we trust the IMU in these cases? In this paper, we present a robust and simple method to calibrate an IMU without any external equipment. We then use the calibration results to analyze the behavior of two types of MEMS based IMUs employed as a single sensor in full 3D orientation and egomotion estimation tasks.

[1]  Oliver J. Woodman,et al.  An introduction to inertial navigation , 2007 .

[2]  Wouter Olthuis,et al.  Procedure for in-use calibration of triaxial accelerometers , 1997 .

[3]  Stefano Soatto,et al.  Visual-inertial ego-motion estimation for humanoid platforms , 2012, 2012 12th IEEE-RAS International Conference on Humanoid Robots (Humanoids 2012).

[4]  John L. Crassidis,et al.  Geometric Integration of Quaternions , 2012 .

[5]  Emanuele Menegatti,et al.  A robust and easy to implement method for IMU calibration without external equipments , 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).

[6]  Andrew Y. C. Nee,et al.  Methods for in-field user calibration of an inertial measurement unit without external equipment , 2008 .

[7]  Michal Reinstein,et al.  Complementary filtering approach to orientation estimation using inertial sensors only , 2012, 2012 IEEE International Conference on Robotics and Automation.

[8]  John Weston,et al.  Strapdown Inertial Navigation Technology , 1997 .

[9]  Isaac Skog,et al.  Calibration of a MEMS inertial measurement unit , 2006 .

[10]  Robert E. Mahony,et al.  Attitude estimation on SO[3] based on direct inertial measurements , 2006, Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006..