360$$^{\circ }$$ Real-Time 3D Multi-object Detection and Tracking for Autonomous Vehicle Navigation

Javier Del Egido; Carlos Gómez-Huélamo; Luis M. Bergasa; Rafael Barea; Elena López-Guillén; Javier Araluce; Rodrigo Gutiérrez; Miguel Antunes

doi:10.1007/978-3-030-62579-5_17

360$$^{\circ }$$ Real-Time 3D Multi-object Detection and Tracking for Autonomous Vehicle Navigation

Javier Del Egido^*
, Carlos Gómez-Huélamo
, Luis M. Bergasa
, Rafael Barea
, Elena López-Guillén
, Javier Araluce
, Rodrigo Gutiérrez
, Miguel Antunes

^*Corresponding author for this work

University of Alcalá

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

Abstract

This paper presents a real-time 3D Multi Object Detection and Tracking (DAMOT) method proposed for the UAH autonomous electric car. It allows the vehicle to recognize 360 surrounding objects and uniquely identify them to be able to follow their trajectory in scene by only receiving a 3D point cloud through ROS framework. First, we describe our proposal of 3D object detector, based on PointPillars [11], processing LiDAR data to locate objects in space obtaining their dimensions and location. Secondly, we use BEV-MOT [7], our Multi-Object Tracking technique in order to uniquely identify each object over a Bird’s-Eye View (BEV) through a combination of 2D Kalman filter and Hungarian algorithm, allowing the ego-vehicle to follow surrounding objects trajectories. A comparison of the performance of our proposal with other state-of-the-art methods is carried out applying KITTI-3DMOT evaluation tool extracted from AB3DMOT [21] on KITTI [5] validation dataset. Finally, we validate our DAMOT in several traffic scenarios implemented in CARLA [4] open-source driving simulator by using AB4COGT tool, designed by authors, studying its performance in a controlled but realistic urban environment with real-time execution, providing several demonstration videos (https://cutt.ly/3rU113d).

Original language	English
Title of host publication	Advances in Physical Agents II - Proceedings of the 21st International Workshop of Physical Agents WAF 2020
Editors	Luis M. Bergasa, Manuel Ocaña, Rafael Barea, Elena López-Guillén, Pedro Revenga
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	241-255
Number of pages	15
ISBN (Print)	9783030625788
DOIs	https://doi.org/10.1007/978-3-030-62579-5_17
Publication status	Published - 2021
Externally published	Yes
Event	21st International Workshop of Physical Agents, WAF 2020 - Alcalá de Henares, Madrid, Spain Duration: 19 Nov 2020 → 20 Nov 2020

Publication series

Name	Advances in Intelligent Systems and Computing
Volume	1285
ISSN (Print)	2194-5357
ISSN (Electronic)	2194-5365

Conference

Conference	21st International Workshop of Physical Agents, WAF 2020
Country/Territory	Spain
City	Alcalá de Henares, Madrid
Period	19/11/20 → 20/11/20

UN SDGs

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

SDG 7 Affordable and Clean Energy

Keywords

3D Multi-object Tracking
Autonomous navigation
CARLA
DAMOT
LiDAR
Real-time
ROS

Access to Document

10.1007/978-3-030-62579-5_17

Cite this

Del Egido, J., Gómez-Huélamo, C., Bergasa, L. M., Barea, R., López-Guillén, E., Araluce, J., Gutiérrez, R., & Antunes, M. (2021). 360$$^{\circ }$$ Real-Time 3D Multi-object Detection and Tracking for Autonomous Vehicle Navigation. In L. M. Bergasa, M. Ocaña, R. Barea, E. López-Guillén, & P. Revenga (Eds.), Advances in Physical Agents II - Proceedings of the 21st International Workshop of Physical Agents WAF 2020 (pp. 241-255). (Advances in Intelligent Systems and Computing; Vol. 1285). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-62579-5_17

Del Egido, Javier ; Gómez-Huélamo, Carlos ; Bergasa, Luis M. et al. / 360$$^{\circ }$$ Real-Time 3D Multi-object Detection and Tracking for Autonomous Vehicle Navigation. Advances in Physical Agents II - Proceedings of the 21st International Workshop of Physical Agents WAF 2020. editor / Luis M. Bergasa ; Manuel Ocaña ; Rafael Barea ; Elena López-Guillén ; Pedro Revenga. Springer Science and Business Media Deutschland GmbH, 2021. pp. 241-255 (Advances in Intelligent Systems and Computing).

@inproceedings{143f77aafb764333b5b2243d14d174ae,

title = "360\$\$\textasciicircum{}\{\textbackslash{}circ \}\$\$ Real-Time 3D Multi-object Detection and Tracking for Autonomous Vehicle Navigation",

abstract = "This paper presents a real-time 3D Multi Object Detection and Tracking (DAMOT) method proposed for the UAH autonomous electric car. It allows the vehicle to recognize 360 surrounding objects and uniquely identify them to be able to follow their trajectory in scene by only receiving a 3D point cloud through ROS framework. First, we describe our proposal of 3D object detector, based on PointPillars [11], processing LiDAR data to locate objects in space obtaining their dimensions and location. Secondly, we use BEV-MOT [7], our Multi-Object Tracking technique in order to uniquely identify each object over a Bird{\textquoteright}s-Eye View (BEV) through a combination of 2D Kalman filter and Hungarian algorithm, allowing the ego-vehicle to follow surrounding objects trajectories. A comparison of the performance of our proposal with other state-of-the-art methods is carried out applying KITTI-3DMOT evaluation tool extracted from AB3DMOT [21] on KITTI [5] validation dataset. Finally, we validate our DAMOT in several traffic scenarios implemented in CARLA [4] open-source driving simulator by using AB4COGT tool, designed by authors, studying its performance in a controlled but realistic urban environment with real-time execution, providing several demonstration videos (https://cutt.ly/3rU113d).",

keywords = "3D Multi-object Tracking, Autonomous navigation, CARLA, DAMOT, LiDAR, Real-time, ROS",

author = "\{Del Egido\}, Javier and Carlos G{\'o}mez-Hu{\'e}lamo and Bergasa, \{Luis M.\} and Rafael Barea and Elena L{\'o}pez-Guill{\'e}n and Javier Araluce and Rodrigo Guti{\'e}rrez and Miguel Antunes",

note = "Publisher Copyright: {\textcopyright} 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.; 21st International Workshop of Physical Agents, WAF 2020 ; Conference date: 19-11-2020 Through 20-11-2020",

year = "2021",

doi = "10.1007/978-3-030-62579-5\_17",

language = "English",

isbn = "9783030625788",

series = "Advances in Intelligent Systems and Computing",

publisher = "Springer Science and Business Media Deutschland GmbH",

pages = "241--255",

editor = "Bergasa, \{Luis M.\} and Manuel Oca{\~n}a and Rafael Barea and Elena L{\'o}pez-Guill{\'e}n and Pedro Revenga",

booktitle = "Advances in Physical Agents II - Proceedings of the 21st International Workshop of Physical Agents WAF 2020",

address = "Germany",

}

Del Egido, J, Gómez-Huélamo, C, Bergasa, LM, Barea, R, López-Guillén, E, Araluce, J, Gutiérrez, R & Antunes, M 2021, 360$$^{\circ }$$ Real-Time 3D Multi-object Detection and Tracking for Autonomous Vehicle Navigation. in LM Bergasa, M Ocaña, R Barea, E López-Guillén & P Revenga (eds), Advances in Physical Agents II - Proceedings of the 21st International Workshop of Physical Agents WAF 2020. Advances in Intelligent Systems and Computing, vol. 1285, Springer Science and Business Media Deutschland GmbH, pp. 241-255, 21st International Workshop of Physical Agents, WAF 2020, Alcalá de Henares, Madrid, Spain, 19/11/20. https://doi.org/10.1007/978-3-030-62579-5_17

360$$^{\circ }$$ Real-Time 3D Multi-object Detection and Tracking for Autonomous Vehicle Navigation. / Del Egido, Javier; Gómez-Huélamo, Carlos; Bergasa, Luis M. et al.
Advances in Physical Agents II - Proceedings of the 21st International Workshop of Physical Agents WAF 2020. ed. / Luis M. Bergasa; Manuel Ocaña; Rafael Barea; Elena López-Guillén; Pedro Revenga. Springer Science and Business Media Deutschland GmbH, 2021. p. 241-255 (Advances in Intelligent Systems and Computing; Vol. 1285).

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

TY - GEN

T1 - 360$$^{\circ }$$ Real-Time 3D Multi-object Detection and Tracking for Autonomous Vehicle Navigation

AU - Del Egido, Javier

AU - Gómez-Huélamo, Carlos

AU - Bergasa, Luis M.

AU - Barea, Rafael

AU - López-Guillén, Elena

AU - Araluce, Javier

AU - Gutiérrez, Rodrigo

AU - Antunes, Miguel

PY - 2021

Y1 - 2021

N2 - This paper presents a real-time 3D Multi Object Detection and Tracking (DAMOT) method proposed for the UAH autonomous electric car. It allows the vehicle to recognize 360 surrounding objects and uniquely identify them to be able to follow their trajectory in scene by only receiving a 3D point cloud through ROS framework. First, we describe our proposal of 3D object detector, based on PointPillars [11], processing LiDAR data to locate objects in space obtaining their dimensions and location. Secondly, we use BEV-MOT [7], our Multi-Object Tracking technique in order to uniquely identify each object over a Bird’s-Eye View (BEV) through a combination of 2D Kalman filter and Hungarian algorithm, allowing the ego-vehicle to follow surrounding objects trajectories. A comparison of the performance of our proposal with other state-of-the-art methods is carried out applying KITTI-3DMOT evaluation tool extracted from AB3DMOT [21] on KITTI [5] validation dataset. Finally, we validate our DAMOT in several traffic scenarios implemented in CARLA [4] open-source driving simulator by using AB4COGT tool, designed by authors, studying its performance in a controlled but realistic urban environment with real-time execution, providing several demonstration videos (https://cutt.ly/3rU113d).

AB - This paper presents a real-time 3D Multi Object Detection and Tracking (DAMOT) method proposed for the UAH autonomous electric car. It allows the vehicle to recognize 360 surrounding objects and uniquely identify them to be able to follow their trajectory in scene by only receiving a 3D point cloud through ROS framework. First, we describe our proposal of 3D object detector, based on PointPillars [11], processing LiDAR data to locate objects in space obtaining their dimensions and location. Secondly, we use BEV-MOT [7], our Multi-Object Tracking technique in order to uniquely identify each object over a Bird’s-Eye View (BEV) through a combination of 2D Kalman filter and Hungarian algorithm, allowing the ego-vehicle to follow surrounding objects trajectories. A comparison of the performance of our proposal with other state-of-the-art methods is carried out applying KITTI-3DMOT evaluation tool extracted from AB3DMOT [21] on KITTI [5] validation dataset. Finally, we validate our DAMOT in several traffic scenarios implemented in CARLA [4] open-source driving simulator by using AB4COGT tool, designed by authors, studying its performance in a controlled but realistic urban environment with real-time execution, providing several demonstration videos (https://cutt.ly/3rU113d).

KW - 3D Multi-object Tracking

KW - Autonomous navigation

KW - CARLA

KW - DAMOT

KW - LiDAR

KW - Real-time

KW - ROS

UR - https://www.scopus.com/pages/publications/85097402629

U2 - 10.1007/978-3-030-62579-5_17

DO - 10.1007/978-3-030-62579-5_17

M3 - Conference contribution

AN - SCOPUS:85097402629

SN - 9783030625788

T3 - Advances in Intelligent Systems and Computing

SP - 241

EP - 255

BT - Advances in Physical Agents II - Proceedings of the 21st International Workshop of Physical Agents WAF 2020

A2 - Bergasa, Luis M.

A2 - Ocaña, Manuel

A2 - Barea, Rafael

A2 - López-Guillén, Elena

A2 - Revenga, Pedro

PB - Springer Science and Business Media Deutschland GmbH

T2 - 21st International Workshop of Physical Agents, WAF 2020

Y2 - 19 November 2020 through 20 November 2020

ER -

Del Egido J, Gómez-Huélamo C, Bergasa LM, Barea R, López-Guillén E, Araluce J et al. 360$$^{\circ }$$ Real-Time 3D Multi-object Detection and Tracking for Autonomous Vehicle Navigation. In Bergasa LM, Ocaña M, Barea R, López-Guillén E, Revenga P, editors, Advances in Physical Agents II - Proceedings of the 21st International Workshop of Physical Agents WAF 2020. Springer Science and Business Media Deutschland GmbH. 2021. p. 241-255. (Advances in Intelligent Systems and Computing). doi: 10.1007/978-3-030-62579-5_17

360$$^{\circ }$$ Real-Time 3D Multi-object Detection and Tracking for Autonomous Vehicle Navigation

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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