3-D position estimation from inertial sensing: minimizing the error from the process of double integration of accelerations
This addresses a specific challenge in low-cost motion tracking systems for applications like daily life tasks, but it is incremental as it builds on existing methods for error reduction.
The paper tackles the problem of minimizing error in 3-D position estimation from inertial sensing by detecting motion stops to reduce drift from double integration of accelerations, reporting improved accuracy for periods longer than a few seconds in a pick-and-place task.
This paper introduces a new approach to 3-D position estimation from acceleration data, i.e., a 3-D motion tracking system having a small size and low-cost magnetic and inertial measurement unit (MIMU) composed by both a digital compass and a gyroscope as interaction technology. A major challenge is to minimize the error caused by the process of double integration of accelerations due to motion (these ones have to be separated from the accelerations due to gravity). Owing to drift error, position estimation cannot be performed with adequate accuracy for periods longer than few seconds. For this reason, we propose a method to detect motion stops and only integrate accelerations in moments of effective hand motion during the demonstration process. The proposed system is validated and evaluated with experiments reporting a common daily life pick-and-place task.