GPU-accelerated Real-Time 3D Tracking for Humanoid Autonomy

Philipp Michel, Joel Chestnutt, Satoshi Kagami, Koichi Nishiwaki, James Kuffner and Takeo Kanade
Conference Paper, Proceedings of the JSME Robotics and Mechatronics Conference (ROBOMEC'08), June, 2008

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We have accelerated a robust model-based 3D tracking system by programmable graphics hardware to run online at frame-rate during operation of a humanoid robot and to efficiently auto-initialize. The tracker recovers the full 6 degree-of-freedom pose of viewable objects relative to the robot. Leveraging the computational resources of the GPU for perception has enabled us to increase our tracker’s robustness to the significant camera displacement and camera shake typically encountered during humanoid navigation. We have combined our approach with a footstep planner and a controller capable of adaptively adjusting the height of swing leg trajectories. The resulting integrated perception-planning-action system has allowed an HRP-2 humanoid robot to successfully and rapidly localize, approach and climb stairs, as well as to avoid obstacles during walking.

This work was supported by a JSPS Postdoctoral Fellowship

author = {Philipp Michel and Joel Chestnutt and Satoshi Kagami and Koichi Nishiwaki and James Kuffner and Takeo Kanade},
title = {GPU-accelerated Real-Time 3D Tracking for Humanoid Autonomy},
booktitle = {Proceedings of the JSME Robotics and Mechatronics Conference (ROBOMEC'08)},
year = {2008},
month = {June},
keywords = {Humanoid Robotics, Computer Vision, GPU, Tracking, Motion Planning, Real Time},
} 2017-09-13T10:41:36-04:00