Journal
IFAC PAPERSONLINE
Volume 53, Issue 2, Pages 16023-16030Publisher
ELSEVIER
DOI: 10.1016/j.ifacol.2020.12.403
Keywords
Observability; motion estimation; inertial sensors; sensor networks; moving horizon estimation; kinematic constraints; nonlinear systems
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Inertial measurement units are commonly used in a growing number of application fields to track or capture motions of kinematic chains, such as human limbs, exoskeletons or robotic actuators. A major challenge is the presence of magnetic disturbances that results in unreliable magnetometer readings. Recent research revealed that this problem can be overcome by exploitation of kinematic constraints. While typically each segment of the kinematic chain is equipped with an IMU, a novel approach called sparse inertial motion tracking aims at inferring the complete motion states from measurements of a reduced set of sensors. In the present contribution, we combine the magnetometer-free and the sparse approach for real-time motion tracking of double-hinge joint systems with non-parallel joint axes. Analyzing the observability of the system, we find a condition which assures that the relative orientations between all segments are uniquely determined by a kinematic constraint, which contains only the gyroscope readings. Furthermore, we propose a moving-horizon estimator and validate it in a simulation study of four movements, which differ by their degrees of excitation. The results of this study confirm the theoretical conjectures and demonstrate that magnetometer-free sparse inertial real-time motion tracking is feasible under precise and simple excitation conditions. Copyright (C) 2020 The Authors.
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