Tree-based search of the next best view/state for three-dimensional object reconstruction

J. Irving Vasquez-Gomez, L. Enrique Sucar, Rafael Murrieta-Cid, Juan Carlos Herrera-Lozada

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

© 2018, © The Author(s) 2018. Three-dimensional models from real objects have many applications in robotics. To automatically build a three-dimensional model from an object, it is essential to determine where to place the range sensor in order to completely observe the object. However, the view (position and orientation) of the sensor is not sufficient, given that its corresponding robot state needs to be calculated. Additionally, a collision-free trajectory to reach that state is required. In this article, we directly find the state of the robot whose corresponding sensor view observes the object. This method does not require to calculate the inverse kinematics of the robot. Unlike previous approaches, the proposed method guides the search with a tree structure based on a rapidly exploring random tree overcoming previous sampling techniques. In addition, we propose an information metric that improves the reconstruction performance of previous information metrics.
Original languageAmerican English
JournalInternational Journal of Advanced Robotic Systems
DOIs
StatePublished - 13 Feb 2018

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Robots
Sensors
Inverse kinematics
Robotics
Trajectories
Sampling

Cite this

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title = "Tree-based search of the next best view/state for three-dimensional object reconstruction",
abstract = "{\circledC} 2018, {\circledC} The Author(s) 2018. Three-dimensional models from real objects have many applications in robotics. To automatically build a three-dimensional model from an object, it is essential to determine where to place the range sensor in order to completely observe the object. However, the view (position and orientation) of the sensor is not sufficient, given that its corresponding robot state needs to be calculated. Additionally, a collision-free trajectory to reach that state is required. In this article, we directly find the state of the robot whose corresponding sensor view observes the object. This method does not require to calculate the inverse kinematics of the robot. Unlike previous approaches, the proposed method guides the search with a tree structure based on a rapidly exploring random tree overcoming previous sampling techniques. In addition, we propose an information metric that improves the reconstruction performance of previous information metrics.",
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Tree-based search of the next best view/state for three-dimensional object reconstruction. / Vasquez-Gomez, J. Irving; Sucar, L. Enrique; Murrieta-Cid, Rafael; Herrera-Lozada, Juan Carlos.

In: International Journal of Advanced Robotic Systems, 13.02.2018.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Tree-based search of the next best view/state for three-dimensional object reconstruction

AU - Vasquez-Gomez, J. Irving

AU - Sucar, L. Enrique

AU - Murrieta-Cid, Rafael

AU - Herrera-Lozada, Juan Carlos

PY - 2018/2/13

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AB - © 2018, © The Author(s) 2018. Three-dimensional models from real objects have many applications in robotics. To automatically build a three-dimensional model from an object, it is essential to determine where to place the range sensor in order to completely observe the object. However, the view (position and orientation) of the sensor is not sufficient, given that its corresponding robot state needs to be calculated. Additionally, a collision-free trajectory to reach that state is required. In this article, we directly find the state of the robot whose corresponding sensor view observes the object. This method does not require to calculate the inverse kinematics of the robot. Unlike previous approaches, the proposed method guides the search with a tree structure based on a rapidly exploring random tree overcoming previous sampling techniques. In addition, we propose an information metric that improves the reconstruction performance of previous information metrics.

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