A Robust Humanoid Robot Navigation Algorithm with ZUPT

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Conference Proceeding
IEEE International Conference on Mechatronics and Automation, 2012, pp. 505 - 510
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this paper discusses algorithmic concepts, design and testing of a pedestrian dead reckoning (PDR) navigation system based on a low-cost inertial measurement unit (IMU) attached to a userâs shoe. The algorithm uses the technique known as âZero Velocity Updateâ (ZUPT) and Kalman Filter consists of 24 error states to reduce IMU errors. We propose a novel dynamic and more robust algorithm to detect the stance phases during walking. The system works well in both 2D (2-dimensional) and 3D environments. Test results show that its horizontal positioning errors are always below 0.3% of the total travelled distance, and the vertical errors are below 0.7%, even on 3D terrain. These results reach the highest position accuracy in available literature.
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