Correlation flow : robust optical flow using kernel cross-correlators
Robust velocity and position estimation is crucial for autonomous robot navigation. The optical flow based methods for autonomous navigation have been receiving increasing attentions in tandem with the development of micro unmanned aerial vehicles. This paper proposes a kernel cross-correlator (K...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Conference Paper |
| Language: | English |
| Published: |
2020
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/143629 |
| _version_ | 1811692248410095616 |
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| author | Wang, Chen Ji, Tete Nguyen, Thien-Minh Xie, Lihua |
| author2 | School of Electrical and Electronic Engineering |
| author_facet | School of Electrical and Electronic Engineering Wang, Chen Ji, Tete Nguyen, Thien-Minh Xie, Lihua |
| author_sort | Wang, Chen |
| collection | NTU |
| description | Robust velocity and position estimation is crucial for autonomous robot
navigation. The optical flow based methods for autonomous navigation have been
receiving increasing attentions in tandem with the development of micro
unmanned aerial vehicles. This paper proposes a kernel cross-correlator (KCC)
based algorithm to determine optical flow using a monocular camera, which is
named as correlation flow (CF). Correlation flow is able to provide reliable
and accurate velocity estimation and is robust to motion blur. In addition, it
can also estimate the altitude velocity and yaw rate, which are not available
by traditional methods. Autonomous flight tests on a quadcopter show that
correlation flow can provide robust trajectory estimation with very low
processing power. The source codes are released based on the ROS framework. |
| first_indexed | 2024-10-01T06:32:46Z |
| format | Conference Paper |
| id | ntu-10356/143629 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T06:32:46Z |
| publishDate | 2020 |
| record_format | dspace |
| spelling | ntu-10356/1436292020-09-15T02:02:27Z Correlation flow : robust optical flow using kernel cross-correlators Wang, Chen Ji, Tete Nguyen, Thien-Minh Xie, Lihua School of Electrical and Electronic Engineering 2018 IEEE International Conference on Robotics and Automation (ICRA) Engineering::Computer science and engineering Kernel Optical Sensors Robust velocity and position estimation is crucial for autonomous robot navigation. The optical flow based methods for autonomous navigation have been receiving increasing attentions in tandem with the development of micro unmanned aerial vehicles. This paper proposes a kernel cross-correlator (KCC) based algorithm to determine optical flow using a monocular camera, which is named as correlation flow (CF). Correlation flow is able to provide reliable and accurate velocity estimation and is robust to motion blur. In addition, it can also estimate the altitude velocity and yaw rate, which are not available by traditional methods. Autonomous flight tests on a quadcopter show that correlation flow can provide robust trajectory estimation with very low processing power. The source codes are released based on the ROS framework. National Research Foundation (NRF) Accepted version The authors would like to thank Mr. Junjun Wang, Hoang Minh-Chung, and Xu Fang for their help in the experiments. This research was partially supported by the ST Engineering-NTU Corporate Lab funded by the NRF Singapore. 2020-09-15T02:02:27Z 2020-09-15T02:02:27Z 2018 Conference Paper Wang, C., Ji, T., Nguyen, T.-M., & Xie, L. (2018). Correlation flow : robust optical flow using kernel cross-correlators. 2018 IEEE International Conference on Robotics and Automation (ICRA), 836-841. doi:10.1109/ICRA.2018.8460569 978-1-5386-3081-5 https://hdl.handle.net/10356/143629 10.1109/ICRA.2018.8460569 836 841 en © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, in any current or future media, including reprinting/republishing this material for adverstising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at:https://doi.org/10.1109/ICRA.2018.8460569 application/pdf |
| spellingShingle | Engineering::Computer science and engineering Kernel Optical Sensors Wang, Chen Ji, Tete Nguyen, Thien-Minh Xie, Lihua Correlation flow : robust optical flow using kernel cross-correlators |
| title | Correlation flow : robust optical flow using kernel cross-correlators |
| title_full | Correlation flow : robust optical flow using kernel cross-correlators |
| title_fullStr | Correlation flow : robust optical flow using kernel cross-correlators |
| title_full_unstemmed | Correlation flow : robust optical flow using kernel cross-correlators |
| title_short | Correlation flow : robust optical flow using kernel cross-correlators |
| title_sort | correlation flow robust optical flow using kernel cross correlators |
| topic | Engineering::Computer science and engineering Kernel Optical Sensors |
| url | https://hdl.handle.net/10356/143629 |
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