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“3D Sensor-Based Obstacle Detection Comparing Octrees and Point clouds Using CUDA”

Authors: Knut B. Kaldestad, Geir Hovland and David A. Anisi,
Affiliation: University of Agder and ABB
Reference: 2012, Vol 33, No 4, pp. 123-130.

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Keywords: Collision Detection, Industrial Robot, GPU, CUDA

Abstract: This paper presents adaptable methods for achieving fast collision detection using the GPU and Nvidia CUDA together with Octrees. Earlier related work have focused on serial methods, while this paper presents a parallel solution which shows that there is a great increase in time if the number of operations is large. Two different models of the environment and the industrial robot are presented, the first is Octrees at different resolutions, the second is a point cloud representation. The relative merits of the two different world model representations are shown. In particular, the experimental results show the potential of adapting the resolution of the robot and environment models to the task at hand.

PDF PDF (1194 Kb)        DOI: 10.4173/mic.2012.4.1

DOI forward links to this article:
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  title={{3D Sensor-Based Obstacle Detection Comparing Octrees and Point clouds Using CUDA}},
  author={Kaldestad, Knut B. and Hovland, Geir and Anisi, David A.},
  journal={Modeling, Identification and Control},
  publisher={Norwegian Society of Automatic Control}


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