Voxel Map Based Collision Detection for Underwater Manipulators

Matija Rossi; Satja Sivcev; Petar Trslic; Gerard Dooly; Edin Omerdic; Daniel Toal

doi:10.1109/OCEANS.2018.8604574

Voxel Map Based Collision Detection for Underwater Manipulators

Matija Rossi
, Satja Sivcev
, Petar Trslic
, Gerard Dooly
, Edin Omerdic
, Daniel Toal

University of Limerick

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

This paper presents a real-time collision detection algorithm for underwater robotic manipulation. It is capable of detecting collisions between multiple manipulators and between manipulators and obstacles in the workspace. Assuming operations are typically carried out on artificial structures with a known geometry, it is possible to model the environment from a priori known CAD models. The position of objects in the workspace is tracked using a vision based approach that relies on fiducial marker detection. The proposed collision detection method is developed, integrated into a commercial ROV manipulator control system, and successfully evaluated in simulations and experimental setup using a real industry standard underwater manipulator.

Original language	English
Title of host publication	OCEANS 2018 MTS/IEEE Charleston, OCEAN 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781538648148
DOIs	https://doi.org/10.1109/OCEANS.2018.8604574
Publication status	Published - 7 Jan 2019
Event	OCEANS 2018 MTS/IEEE Charleston, OCEANS 2018 - Charleston, United States Duration: 22 Oct 2018 → 25 Oct 2018

Publication series

Name	OCEANS 2018 MTS/IEEE Charleston, OCEAN 2018

Conference

Conference	OCEANS 2018 MTS/IEEE Charleston, OCEANS 2018
Country/Territory	United States
City	Charleston
Period	22/10/18 → 25/10/18

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Collision avoidance
Collision detection
Collision sensing
Fiducial markers
Machine vision
Manipulator control
Marine robotics
ROV
Robot arm
Subsea inspection and intervention
Underwater manipulation

Access to Document

10.1109/OCEANS.2018.8604574

Cite this

@inproceedings{247a7d72b2a2468ab9fff263a01150af,

title = "Voxel Map Based Collision Detection for Underwater Manipulators",

abstract = "This paper presents a real-time collision detection algorithm for underwater robotic manipulation. It is capable of detecting collisions between multiple manipulators and between manipulators and obstacles in the workspace. Assuming operations are typically carried out on artificial structures with a known geometry, it is possible to model the environment from a priori known CAD models. The position of objects in the workspace is tracked using a vision based approach that relies on fiducial marker detection. The proposed collision detection method is developed, integrated into a commercial ROV manipulator control system, and successfully evaluated in simulations and experimental setup using a real industry standard underwater manipulator.",

keywords = "Collision avoidance, Collision detection, Collision sensing, Fiducial markers, Machine vision, Manipulator control, Marine robotics, ROV, Robot arm, Subsea inspection and intervention, Underwater manipulation",

author = "Matija Rossi and Satja Sivcev and Petar Trslic and Gerard Dooly and Edin Omerdic and Daniel Toal",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; OCEANS 2018 MTS/IEEE Charleston, OCEANS 2018 ; Conference date: 22-10-2018 Through 25-10-2018",

year = "2019",

month = jan,

day = "7",

doi = "10.1109/OCEANS.2018.8604574",

language = "English",

series = "OCEANS 2018 MTS/IEEE Charleston, OCEAN 2018",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "OCEANS 2018 MTS/IEEE Charleston, OCEAN 2018",

}

Rossi, M, Sivcev, S, Trslic, P , Dooly, G , Omerdic, E & Toal, D 2019, Voxel Map Based Collision Detection for Underwater Manipulators. in OCEANS 2018 MTS/IEEE Charleston, OCEAN 2018., 8604574, OCEANS 2018 MTS/IEEE Charleston, OCEAN 2018, Institute of Electrical and Electronics Engineers Inc., OCEANS 2018 MTS/IEEE Charleston, OCEANS 2018, Charleston, United States, 22/10/18. https://doi.org/10.1109/OCEANS.2018.8604574

Voxel Map Based Collision Detection for Underwater Manipulators. / Rossi, Matija; Sivcev, Satja; Trslic, Petar et al.
OCEANS 2018 MTS/IEEE Charleston, OCEAN 2018. Institute of Electrical and Electronics Engineers Inc., 2019. 8604574 (OCEANS 2018 MTS/IEEE Charleston, OCEAN 2018).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Voxel Map Based Collision Detection for Underwater Manipulators

AU - Rossi, Matija

AU - Sivcev, Satja

AU - Trslic, Petar

AU - Dooly, Gerard

AU - Omerdic, Edin

AU - Toal, Daniel

PY - 2019/1/7

Y1 - 2019/1/7

N2 - This paper presents a real-time collision detection algorithm for underwater robotic manipulation. It is capable of detecting collisions between multiple manipulators and between manipulators and obstacles in the workspace. Assuming operations are typically carried out on artificial structures with a known geometry, it is possible to model the environment from a priori known CAD models. The position of objects in the workspace is tracked using a vision based approach that relies on fiducial marker detection. The proposed collision detection method is developed, integrated into a commercial ROV manipulator control system, and successfully evaluated in simulations and experimental setup using a real industry standard underwater manipulator.

AB - This paper presents a real-time collision detection algorithm for underwater robotic manipulation. It is capable of detecting collisions between multiple manipulators and between manipulators and obstacles in the workspace. Assuming operations are typically carried out on artificial structures with a known geometry, it is possible to model the environment from a priori known CAD models. The position of objects in the workspace is tracked using a vision based approach that relies on fiducial marker detection. The proposed collision detection method is developed, integrated into a commercial ROV manipulator control system, and successfully evaluated in simulations and experimental setup using a real industry standard underwater manipulator.

KW - Collision avoidance

KW - Collision detection

KW - Collision sensing

KW - Fiducial markers

KW - Machine vision

KW - Manipulator control

KW - Marine robotics

KW - ROV

KW - Robot arm

KW - Subsea inspection and intervention

KW - Underwater manipulation

UR - https://www.scopus.com/pages/publications/85061781981

U2 - 10.1109/OCEANS.2018.8604574

DO - 10.1109/OCEANS.2018.8604574

M3 - Conference contribution

AN - SCOPUS:85061781981

T3 - OCEANS 2018 MTS/IEEE Charleston, OCEAN 2018

BT - OCEANS 2018 MTS/IEEE Charleston, OCEAN 2018

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - OCEANS 2018 MTS/IEEE Charleston, OCEANS 2018

Y2 - 22 October 2018 through 25 October 2018

ER -

Voxel Map Based Collision Detection for Underwater Manipulators

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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Cite this