3D posture estimation for a hose-shaped robot is critical in rescue activities due to complex physical environments. Conventional sound-based posture estimation assumes rather flat physical environments and focuses only on 2D, resulting in poor performance in real world environments with rubble. This paper presents novel 3D posture estimation by exploiting microphones and accelerometers. The idea of our method is to compensate the lack of posture information obtained by sound-based time-difference-of arrival (TDOA) with the tilt information obtained from accelerometers. This compensation is formulated as a nonlinear state-space model and solved by the unscented Kalman filter. Experiments are conducted by using a 3m hose-shaped robot with eight units of a microphone and an accelerometer and seven units of a loudspeaker and a vibration motor deployed in a simple 3D structure. Experimental results demonstrate that our method reduces the errors of initial states to about 20 cm in the 3D space. If the initial errors of initial states are less than 20 %, our method can estimate the correct 3D posture in real-time.
|Title of host publication
|IEEE International Conference on Intelligent Robots and Systems
|Institute of Electrical and Electronics Engineers Inc.
|Number of pages
|Published - 2015 Dec 11
|IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2015 - Hamburg, Germany
Duration: 2015 Sept 28 → 2015 Oct 2
|IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2015
|15/9/28 → 15/10/2
- Robot sensing systems
- Three-dimensional displays
ASJC Scopus subject areas
- Control and Systems Engineering
- Computer Vision and Pattern Recognition
- Computer Science Applications