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

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 ope...

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Main Authors: K.B. Kaldestad, G. Hovland, D.A. Anisi
Format: Article
Language:English
Published: Norwegian Society of Automatic Control 2012-10-01
Series:Modeling, Identification and Control
Subjects:
Online Access:http://www.mic-journal.no/PDF/2012/MIC-2012-4-1.pdf
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author K.B. Kaldestad
G. Hovland
D.A. Anisi
author_facet K.B. Kaldestad
G. Hovland
D.A. Anisi
author_sort K.B. Kaldestad
collection DOAJ
description 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.
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1890-1328
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spelling doaj.art-7f02a6db2ab945d39cc024f5bc06206f2022-12-21T21:53:13ZengNorwegian Society of Automatic ControlModeling, Identification and Control0332-73531890-13282012-10-0133412313010.4173/mic.2012.4.13D Sensor-Based Obstacle Detection Comparing Octrees and Point clouds Using CUDAK.B. KaldestadG. HovlandD.A. AnisiThis 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.http://www.mic-journal.no/PDF/2012/MIC-2012-4-1.pdfCollision DetectionIndustrial RobotGPU
spellingShingle K.B. Kaldestad
G. Hovland
D.A. Anisi
3D Sensor-Based Obstacle Detection Comparing Octrees and Point clouds Using CUDA
Modeling, Identification and Control
Collision Detection
Industrial Robot
GPU
title 3D Sensor-Based Obstacle Detection Comparing Octrees and Point clouds Using CUDA
title_full 3D Sensor-Based Obstacle Detection Comparing Octrees and Point clouds Using CUDA
title_fullStr 3D Sensor-Based Obstacle Detection Comparing Octrees and Point clouds Using CUDA
title_full_unstemmed 3D Sensor-Based Obstacle Detection Comparing Octrees and Point clouds Using CUDA
title_short 3D Sensor-Based Obstacle Detection Comparing Octrees and Point clouds Using CUDA
title_sort 3d sensor based obstacle detection comparing octrees and point clouds using cuda
topic Collision Detection
Industrial Robot
GPU
url http://www.mic-journal.no/PDF/2012/MIC-2012-4-1.pdf
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AT ghovland 3dsensorbasedobstacledetectioncomparingoctreesandpointcloudsusingcuda
AT daanisi 3dsensorbasedobstacledetectioncomparingoctreesandpointcloudsusingcuda