GPU-accelerated Real-Time 3D Tracking for Humanoid Locomotion and Stair Climbing

Philipp Michel, Joel Chestnutt, Satoshi Kagami, Koichi Nishiwaki, James Kuffner and Takeo Kanade
Conference Paper, Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'07), pp. 463-469, October, 2007

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For humanoid robots to fully realize their biped potential in a three-dimensional world and step over, around or onto obstacles such as stairs, appropriate and efficient approaches to execution, planning and perception are required. To this end, we have accelerated a robust model-based three-dimensional tracking system by programmable graphics hardware to operate online at frame-rate during locomotion of a humanoid robot. 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 an NVIDIA 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 Locomotion and Stair Climbing},
booktitle = {Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'07)},
year = {2007},
month = {October},
pages = {463-469},
keywords = {Humanoid Robots, Humanoids, Computer Vision, GPU, Tracking, Perception, Locomotion},
} 2017-09-13T10:41:57-04:00