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@article{ART003029470},
author={JIN YOUNG HOON},
title={Designing a Reinforcement Learning-Based 3D Object Reconstruction Data Acquisition Simulation},
journal={Journal of Internet of Things and Convergence},
issn={2466-0078},
year={2023},
volume={9},
number={6},
pages={11-16},
doi={10.20465/KIOTS.2023.9.6.011}

TY - JOUR
AU - JIN YOUNG HOON
TI - Designing a Reinforcement Learning-Based 3D Object Reconstruction Data Acquisition Simulation
JO - Journal of Internet of Things and Convergence
PY - 2023
VL - 9
IS - 6
PB - The Korea Internet of Things Society
SP - 11
EP - 16
SN - 2466-0078
AB - The technology of 3D reconstruction, primarily relying on point cloud data, is essential for digitizing objects or spaces. This paper aims to utilize reinforcement learning to achieve the acquisition of point clouds in a given environment. To accomplish this, a simulation environment is constructed using Unity, and reinforcement learning is implemented using the Unity package known as ML-Agents. The process of point cloud acquisition involves initially setting a goal and calculating a traversable path around the goal. The traversal path is segmented at regular intervals, with rewards assigned at each step. To prevent the agent from deviating from the path, rewards are increased. Additionally, rewards are granted each time the agent fixates on the goal during traversal, facilitating the learning of optimal points for point cloud acquisition at each traversal step. Experimental results demonstrate that despite the variability in traversal paths, the approach enables the acquisition of relatively accurate point clouds.
KW - Unity3D;ML-Agents;Point Cloud;Reinforcement Learning;Bot;Autonomous Driving
DO - 10.20465/KIOTS.2023.9.6.011
ER -

JIN YOUNG HOON. (2023). Designing a Reinforcement Learning-Based 3D Object Reconstruction Data Acquisition Simulation. Journal of Internet of Things and Convergence, 9(6), 11-16.

JIN YOUNG HOON. 2023, "Designing a Reinforcement Learning-Based 3D Object Reconstruction Data Acquisition Simulation", Journal of Internet of Things and Convergence, vol.9, no.6 pp.11-16. Available from: doi:10.20465/KIOTS.2023.9.6.011

JIN YOUNG HOON "Designing a Reinforcement Learning-Based 3D Object Reconstruction Data Acquisition Simulation" Journal of Internet of Things and Convergence 9.6 pp.11-16 (2023) : 11.

JIN YOUNG HOON. Designing a Reinforcement Learning-Based 3D Object Reconstruction Data Acquisition Simulation. 2023; 9(6), 11-16. Available from: doi:10.20465/KIOTS.2023.9.6.011

JIN YOUNG HOON. "Designing a Reinforcement Learning-Based 3D Object Reconstruction Data Acquisition Simulation" Journal of Internet of Things and Convergence 9, no.6 (2023) : 11-16.doi: 10.20465/KIOTS.2023.9.6.011

JIN YOUNG HOON. Designing a Reinforcement Learning-Based 3D Object Reconstruction Data Acquisition Simulation. Journal of Internet of Things and Convergence, 9(6), 11-16. doi: 10.20465/KIOTS.2023.9.6.011

JIN YOUNG HOON. Designing a Reinforcement Learning-Based 3D Object Reconstruction Data Acquisition Simulation. Journal of Internet of Things and Convergence. 2023; 9(6) 11-16. doi: 10.20465/KIOTS.2023.9.6.011

JIN YOUNG HOON. Designing a Reinforcement Learning-Based 3D Object Reconstruction Data Acquisition Simulation. 2023; 9(6), 11-16. Available from: doi:10.20465/KIOTS.2023.9.6.011

JIN YOUNG HOON. "Designing a Reinforcement Learning-Based 3D Object Reconstruction Data Acquisition Simulation" Journal of Internet of Things and Convergence 9, no.6 (2023) : 11-16.doi: 10.20465/KIOTS.2023.9.6.011