research-article

A Solution to the Next Best View Problem for Automated Surface Acquisition

Author:

Richard PitoAuthors Info & Claims

IEEE Transactions on Pattern Analysis and Machine Intelligence, Volume 21, Issue 10

Pages 1016 - 1030

https://doi.org/10.1109/34.799908

Published: 01 October 1999 Publication History

Abstract

A solution to the next best view (NBV) problem for automated surface acquisition is presented. The NBV problem is to determine which areas of a scanner's viewing volume need to be scanned to sample all of the visible surfaces of an a priori unknown object and where to position/control the scanner to sample them. It is argued that solutions to the NBV problem are constrained by the other steps in a surface acquisition system and by the range scanner's particular sampling physics. A method for determining the unscanned areas of the viewing volume is presented. In addition, a novel representation, positional space (PS), is presented which facilitates a solution to the NBV problem by representing what must be and what can be scanned in a single data structure. The number of costly computations needed to determine if an area of the viewing volume would be occluded from some scanning position is decoupled from the number of positions considered for the NBV, thus reducing the computational cost of choosing one. An automated surface acquisition systems designed to scan all visible surfaces of an a priori unknown object is demonstrated on real objects.

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Index Terms

A Solution to the Next Best View Problem for Automated Surface Acquisition
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
  2. Computer graphics
    1. Shape modeling
      1. Parametric curve and surface models
      2. Volumetric models

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Published In

cover image IEEE Transactions on Pattern Analysis and Machine Intelligence

IEEE Transactions on Pattern Analysis and Machine Intelligence Volume 21, Issue 10

October 1999

141 pages

ISSN:0162-8828

Editor:
Kevin Bowyer
Univ. of South Florida, Tampa

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Copyright © Copyright © 1999 IEEE. All Rights Reserved.

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IEEE Computer Society

United States

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Published: 01 October 1999

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Cited By

Lindqvist BPatel ALöfgren KNikolakopoulos G(2024)A Tree-Based Next-Best-Trajectory Method for 3-D UAV ExplorationIEEE Transactions on Robotics10.1109/TRO.2024.342205240(3496-3513)Online publication date: 1-Jan-2024
https://dl.acm.org/doi/10.1109/TRO.2024.3422052
Patel AKarlsson SLindqvist BHaluska JKanellakis CAgha-mohammadi ANikolakopoulos G(2024)Towards field deployment of MAVs in adaptive exploration of GPS-denied subterranean environmentsRobotics and Autonomous Systems10.1016/j.robot.2024.104663176:COnline publication date: 1-Jun-2024
https://dl.acm.org/doi/10.1016/j.robot.2024.104663
Placed JStrader JCarrillo HAtanasov NIndelman VCarlone LCastellanos J(2023)A Survey on Active Simultaneous Localization and Mapping: State of the Art and New FrontiersIEEE Transactions on Robotics10.1109/TRO.2023.324851039:3(1686-1705)Online publication date: 1-Jun-2023
https://dl.acm.org/doi/10.1109/TRO.2023.3248510
Pan SWei H(2023)A global generalized maximum coverage-based solution to the non-model-based view planning problem for object reconstructionComputer Vision and Image Understanding10.1016/j.cviu.2022.103585226:COnline publication date: 1-Jan-2023
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Patel ALindqvist BKanellakis CAgha-mohammadi ANikolakopoulos G(2023)REF: A Rapid Exploration Framework for Deploying Autonomous MAVs in Unknown EnvironmentsJournal of Intelligent and Robotic Systems10.1007/s10846-023-01836-z108:3Online publication date: 20-Jun-2023
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Lehnert CTsai DEriksson AMcCool C(2022)3D Move to See: Multi-perspective visual servoing towards the next best view within unstructured and occluded environments2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)10.1109/IROS40897.2019.8967918(3890-3897)Online publication date: 28-Dec-2022
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Han YZhan IZhao WLiu Y(2022)A Double Branch Next-Best-View Network and Novel Robot System for Active Object Reconstruction2022 International Conference on Robotics and Automation (ICRA)10.1109/ICRA46639.2022.9811769(7306-7312)Online publication date: 23-May-2022
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Yervilla-Herrera HBecerra IMurrieta-Cid RSucar LMorales E(2022)Bayesian Probabilistic Stopping Test and Asymptotic Shortest Time Trajectories for Object Reconstruction with a Mobile Manipulator RobotJournal of Intelligent and Robotic Systems10.1007/s10846-022-01696-z105:4Online publication date: 1-Aug-2022
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Fukusato TMaejima A(2021)Interactive Viewpoint Exploration for Constructing View-Dependent ModelsProceedings of the 14th ACM SIGGRAPH Conference on Motion, Interaction and Games10.1145/3487983.3488287(1-8)Online publication date: 10-Nov-2021
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