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Article: FPGA-based High-Performance Collision Detection: An Enabling Technique for Image-Guided Robotic Surgery

TitleFPGA-based High-Performance Collision Detection: An Enabling Technique for Image-Guided Robotic Surgery
Authors
KeywordsCollision detection
Computer vision
CPU
FPGA
OBB
Robotic-assisted laparoscopy
Sweep and Prune
Issue Date2016
PublisherFrontiers Research Foundation. The Journal's web site is located at http://www.frontiersin.org/Robotics_and_AI
Citation
Frontiers in Robotics and AI, 2016, v. 3, p. article no. 51 How to Cite?
AbstractCollision detection, which refers to the computational problem of finding the relative placement or con-figuration of two or more objects, is an essential component of many applications in computer graphics and robotics. In image-guided robotic surgery, real-time collision detection is critical for preserving healthy anatomical structures during the surgical procedure. However, the computational complexity of the problem usually results in algorithms that operate at low speed. In this paper, we present a fast and accurate algorithm for collision detection between Oriented-Bounding-Boxes (OBBs) that is suitable for real-time implementation. Our proposed Sweep and Prune algorithm can perform a preliminary filtering to reduce the number of objects that need to be tested by the classical Separating Axis Test algorithm, while the OBB pairs of interest are preserved. These OBB pairs are re-checked by the Separating Axis Test algorithm to obtain accurate overlapping status between them. To accelerate the execution, our Sweep and Prune algorithm is tailor-made for the proposed method. Meanwhile, a high performance scalable hardware architecture is proposed by analyzing the intrinsic parallelism of our algorithm, and is implemented on FPGA platform. Results show that our hardware design on the FPGA platform can achieve around 8X higher running speed than the software design on a CPU platform. As a result, the proposed algorithm can achieve a collision frame rate of 1 KHz, and fulfill the requirement for the medical surgery scenario of Robot Assisted Laparoscopy.
Persistent Identifierhttp://hdl.handle.net/10722/231940
ISSN
2023 Impact Factor: 2.9
2023 SCImago Journal Rankings: 0.809
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorZhang, Z-
dc.contributor.authorXin, Y-
dc.contributor.authorLiu, B-
dc.contributor.authorLi, WXY-
dc.contributor.authorLee, KH-
dc.contributor.authorNg, CF-
dc.contributor.authorStoyanov, D-
dc.contributor.authorCheung, RCC-
dc.contributor.authorKwok, KW-
dc.date.accessioned2016-09-20T05:26:30Z-
dc.date.available2016-09-20T05:26:30Z-
dc.date.issued2016-
dc.identifier.citationFrontiers in Robotics and AI, 2016, v. 3, p. article no. 51-
dc.identifier.issn2296-9144-
dc.identifier.urihttp://hdl.handle.net/10722/231940-
dc.description.abstractCollision detection, which refers to the computational problem of finding the relative placement or con-figuration of two or more objects, is an essential component of many applications in computer graphics and robotics. In image-guided robotic surgery, real-time collision detection is critical for preserving healthy anatomical structures during the surgical procedure. However, the computational complexity of the problem usually results in algorithms that operate at low speed. In this paper, we present a fast and accurate algorithm for collision detection between Oriented-Bounding-Boxes (OBBs) that is suitable for real-time implementation. Our proposed Sweep and Prune algorithm can perform a preliminary filtering to reduce the number of objects that need to be tested by the classical Separating Axis Test algorithm, while the OBB pairs of interest are preserved. These OBB pairs are re-checked by the Separating Axis Test algorithm to obtain accurate overlapping status between them. To accelerate the execution, our Sweep and Prune algorithm is tailor-made for the proposed method. Meanwhile, a high performance scalable hardware architecture is proposed by analyzing the intrinsic parallelism of our algorithm, and is implemented on FPGA platform. Results show that our hardware design on the FPGA platform can achieve around 8X higher running speed than the software design on a CPU platform. As a result, the proposed algorithm can achieve a collision frame rate of 1 KHz, and fulfill the requirement for the medical surgery scenario of Robot Assisted Laparoscopy.-
dc.languageeng-
dc.publisherFrontiers Research Foundation. The Journal's web site is located at http://www.frontiersin.org/Robotics_and_AI-
dc.relation.ispartofFrontiers in Robotics and AI-
dc.rightsThis Document is Protected by copyright and was first published by Frontiers. All rights reserved. It is reproduced with permission.-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectCollision detection-
dc.subjectComputer vision-
dc.subjectCPU-
dc.subjectFPGA-
dc.subjectOBB-
dc.subjectRobotic-assisted laparoscopy-
dc.subjectSweep and Prune-
dc.titleFPGA-based High-Performance Collision Detection: An Enabling Technique for Image-Guided Robotic Surgery-
dc.typeArticle-
dc.identifier.emailNg, CF: ncf0000@hku.hk-
dc.identifier.emailKwok, KW: kwokkw@hku.hk-
dc.identifier.authorityKwok, KW=rp01924-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.3389/frobt.2016.00051-
dc.identifier.scopuseid_2-s2.0-85046950089-
dc.identifier.hkuros265028-
dc.identifier.volume3-
dc.identifier.issue51-
dc.identifier.spagearticle no. 51-
dc.identifier.epagearticle no. 51-
dc.identifier.isiWOS:000384349000001-
dc.publisher.placeSwitzerland-
dc.identifier.issnl2296-9144-

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