A Dynamic Object Removal and Reconstruction Algorithm for Point Clouds

Sarat Chandra  Nagavarapu; Anuj  Abraham; Nithish Muthuchamy  Selvaraj; Justin Dauwels

doi:10.1109/SOLI60636.2023.10425733

A Dynamic Object Removal and Reconstruction Algorithm for Point Clouds

Sarat Chandra Nagavarapu, Anuj Abraham, Nithish Muthuchamy Selvaraj, Justin Dauwels

Signal Processing Systems

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

Abstract

Autonomous vehicles (AV) are one of the greatest technological advancements of this decade and a giant leap in the transportation industry and mobile robotics. Autonomous vehicles face several major challenges in achieving higher levels of autonomy. One of these is to find a fast and reliable algorithm to process the sensor data so that the simultaneous localization and mapping (SLAM) algorithms run in real-time to achieve autonomous navigation. The major limitation of the SLAM algorithm, especially while building a map is to have static environmental features, i.e. without any dynamic or moving objects. To achieve this, our paper introduces a novel algorithm to remove dynamic objects from point cloud data. The algorithm focuses on identifying and removing dynamic objects from sensor data, thereby creating a static scene suitable for traditional SLAM algorithms. Simulations conducted on the benchmark dataset demonstrate the algorithm's efficacy in successfully eliminating dynamic objects and reconstructing a stable static scene.

Original language	English
Title of host publication	Proceedings of the 2023 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI)
Place of Publication	Piscataway
Publisher	IEEE
Number of pages	8
ISBN (Electronic)	979-8-3503-9600-3
ISBN (Print)	979-8-3503-9601-0
DOIs	https://doi.org/10.1109/SOLI60636.2023.10425733
Publication status	Published - 2023
Event	2023 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI) - , Singapore Duration: 11 Dec 2023 → 13 Dec 2023

Publication series

Name	Proceedings of the 17th IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2023

Conference

Conference	2023 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI)
Country/Territory	Singapore
Period	11/12/23 → 13/12/23

Bibliographical note

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Keywords

point clouds
autonomous vehicles
object removal
reconstruction
SLAM
LiDAR
mobile robots

Access to Document

10.1109/SOLI60636.2023.10425733

Cite this

Nagavarapu, S. C., Abraham, A., Selvaraj, N. M., & Dauwels, J. (2023). A Dynamic Object Removal and Reconstruction Algorithm for Point Clouds. In Proceedings of the 2023 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI) (Proceedings of the 17th IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2023). IEEE. https://doi.org/10.1109/SOLI60636.2023.10425733

Nagavarapu, Sarat Chandra ; Abraham, Anuj ; Selvaraj, Nithish Muthuchamy et al. / A Dynamic Object Removal and Reconstruction Algorithm for Point Clouds. Proceedings of the 2023 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI). Piscataway : IEEE, 2023. (Proceedings of the 17th IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2023).

@inproceedings{38b7e09fa1084336a7018a8d87768ea3,

title = "A Dynamic Object Removal and Reconstruction Algorithm for Point Clouds",

abstract = "Autonomous vehicles (AV) are one of the greatest technological advancements of this decade and a giant leap in the transportation industry and mobile robotics. Autonomous vehicles face several major challenges in achieving higher levels of autonomy. One of these is to find a fast and reliable algorithm to process the sensor data so that the simultaneous localization and mapping (SLAM) algorithms run in real-time to achieve autonomous navigation. The major limitation of the SLAM algorithm, especially while building a map is to have static environmental features, i.e. without any dynamic or moving objects. To achieve this, our paper introduces a novel algorithm to remove dynamic objects from point cloud data. The algorithm focuses on identifying and removing dynamic objects from sensor data, thereby creating a static scene suitable for traditional SLAM algorithms. Simulations conducted on the benchmark dataset demonstrate the algorithm's efficacy in successfully eliminating dynamic objects and reconstructing a stable static scene.",

keywords = "point clouds, autonomous vehicles, object removal, reconstruction, SLAM, LiDAR, mobile robots",

author = "Nagavarapu, {Sarat Chandra} and Anuj Abraham and Selvaraj, {Nithish Muthuchamy} and Justin Dauwels",

note = "Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.; 2023 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI) ; Conference date: 11-12-2023 Through 13-12-2023",

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doi = "10.1109/SOLI60636.2023.10425733",

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isbn = "979-8-3503-9601-0",

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Nagavarapu, SC, Abraham, A, Selvaraj, NM & Dauwels, J 2023, A Dynamic Object Removal and Reconstruction Algorithm for Point Clouds. in Proceedings of the 2023 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI). Proceedings of the 17th IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2023, IEEE, Piscataway, 2023 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI), Singapore, 11/12/23. https://doi.org/10.1109/SOLI60636.2023.10425733

A Dynamic Object Removal and Reconstruction Algorithm for Point Clouds. / Nagavarapu, Sarat Chandra ; Abraham, Anuj ; Selvaraj, Nithish Muthuchamy et al.
Proceedings of the 2023 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI). Piscataway: IEEE, 2023. (Proceedings of the 17th IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2023).

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

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AU - Selvaraj, Nithish Muthuchamy

AU - Dauwels, Justin

N1 - Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

PY - 2023

Y1 - 2023

N2 - Autonomous vehicles (AV) are one of the greatest technological advancements of this decade and a giant leap in the transportation industry and mobile robotics. Autonomous vehicles face several major challenges in achieving higher levels of autonomy. One of these is to find a fast and reliable algorithm to process the sensor data so that the simultaneous localization and mapping (SLAM) algorithms run in real-time to achieve autonomous navigation. The major limitation of the SLAM algorithm, especially while building a map is to have static environmental features, i.e. without any dynamic or moving objects. To achieve this, our paper introduces a novel algorithm to remove dynamic objects from point cloud data. The algorithm focuses on identifying and removing dynamic objects from sensor data, thereby creating a static scene suitable for traditional SLAM algorithms. Simulations conducted on the benchmark dataset demonstrate the algorithm's efficacy in successfully eliminating dynamic objects and reconstructing a stable static scene.

AB - Autonomous vehicles (AV) are one of the greatest technological advancements of this decade and a giant leap in the transportation industry and mobile robotics. Autonomous vehicles face several major challenges in achieving higher levels of autonomy. One of these is to find a fast and reliable algorithm to process the sensor data so that the simultaneous localization and mapping (SLAM) algorithms run in real-time to achieve autonomous navigation. The major limitation of the SLAM algorithm, especially while building a map is to have static environmental features, i.e. without any dynamic or moving objects. To achieve this, our paper introduces a novel algorithm to remove dynamic objects from point cloud data. The algorithm focuses on identifying and removing dynamic objects from sensor data, thereby creating a static scene suitable for traditional SLAM algorithms. Simulations conducted on the benchmark dataset demonstrate the algorithm's efficacy in successfully eliminating dynamic objects and reconstructing a stable static scene.

KW - point clouds

KW - autonomous vehicles

KW - object removal

KW - reconstruction

KW - SLAM

KW - LiDAR

KW - mobile robots

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DO - 10.1109/SOLI60636.2023.10425733

M3 - Conference contribution

SN - 979-8-3503-9601-0

T3 - Proceedings of the 17th IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2023

BT - Proceedings of the 2023 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI)

PB - IEEE

CY - Piscataway

T2 - 2023 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI)

Y2 - 11 December 2023 through 13 December 2023

ER -

Nagavarapu SC, Abraham A, Selvaraj NM, Dauwels J. A Dynamic Object Removal and Reconstruction Algorithm for Point Clouds. In Proceedings of the 2023 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI). Piscataway: IEEE. 2023. (Proceedings of the 17th IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2023). doi: 10.1109/SOLI60636.2023.10425733

A Dynamic Object Removal and Reconstruction Algorithm for Point Clouds

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