Dr. Muhammad Zeshan Afzal

Prof. Dr. Didier Stricker

Dr. Alain Pagani

Keonna Cunningham

Dr. Oliver Wasenmüller

Dr. Gabriele Bleser

Dr. Bruno Mirbach

Dr. Jason Raphael Rambach

Dr. Bertram Taetz

Mhd Rashed Al Koutayni

Jilliam Maria Diaz Barros

Iuliia Brishtel

Mahdi Chamseddine

Steve Dias da Cruz

Ahmet Firintepe

Sophie Folawiyo

David Michael Fürst

Kamalveerkaur Garewal

Christiano Couto Gava

Leif Eric Goebel

Tewodros Amberbir Habtegebrial

Jigyasa Singh Katrolia

Andreas Kölsch

Onorina Kovalenko

Muhammad Jameel Nawaz Malik

Nareg Minaskan Karabid

Mohammad Minouei

Manthan Pancholi

Engr. Kumail Raza

Dr. Nadia Robertini

María Alejandra Sánchez Marín

Dr. Kripasindhu Sarkar

Alexander Schäfer

Pascal Schneider

Lukas Stefan Staecker

Dr. Vladislav Golyanik

Dr. Aditya Tewari

André Luiz Brandão

Intelligent Sensor Fusion with Online Distributed MIMU Calibration for Wearable Motion Capture

Intelligent Sensor Fusion with Online Distributed MIMU Calibration for Wearable Motion Capture
Hammad Tanveer Butt, Mathias Musahl, Manthan Pancholi, Pramod Narasimha Murthy, Maria Alejandra Sanchez Marin, Didier Stricker
22nd International Conference on Information Fusion (Fusion-2019), IEEE. International Conference on Information Fusion (FUSION-2019) July 2-5 Ottawa Ontario Canada IEEE 7/2019 .

Abstract:: Wearable systems for human motion capture based on low cost micro-electromechanical magnetic-inertial measurement units (MIMUs) show degraded performance when these systems are run for long time, especially indoors. The limitation arises due to the inhomogeneous magnetic field in the indoor environment, the high dynamic accelerations of body segments and due to bias variation of low cost sensors over time and with temperature. In our approach, we perform sensor fusion and online self-recalibration of accelerometers, magnetometers and rate gyros in a distributed algorithm, in order to provide an accurate orientation estimate. We developed a novel approach to use quasi-static time steps for calibration of rate gyros. To do this, an auto-calibration algorithm runs on each sensing node and provides correction to rate gyro biases. Together a hybrid sensor fusion and calibration algorithm is run on the hub for every sensor node. Our sensor fusion uses a novel adaptive covariance based EKF which makes it robust to both dynamic body accelerations as well as disturbed magnetic field. It also intelligently updates the accelerometer and magnetometer, when disturbances are low. This self-recalibration feature of our algorithm helps to achieve precise orientation estimates in highly dynamic conditions and avoid drift or error accumulation in inhomogeneous magnetic fields.

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