Abstract
This paper describes the design, analysis, and experimental evaluation of a new method to integrate measurements from light detection and ranging (LiDAR) and inertial measurement units (IMU). A tight IMU/LiDAR integration scheme is developed, which aims at exploiting the complementary properties of the two sensors while facilitating safety risk evaluation. In particular, the IMU is used to improve LiDAR position and orientation prediction (or pose), thereby reducing the the risk of incorrectly associating sensed features with mapped landmarks. Conversely, LiDAR pose estimation updates can limit the drift of IMU errors over time. In order to further improve data association, LiDAR return-light intensity measurements are incorporated, which helps distinguish landmarks and thus reduces the risk of incorrect associations. The new method is evaluated and analyzed using experimental data.
| Original language | English (US) |
|---|---|
| Title of host publication | Proceedings of the 32nd International Technical Meeting of the Satellite Division of the Institute of Navigation, ION GNSS+ 2019 |
| Publisher | Institute of Navigation |
| Pages | 2637-2658 |
| Number of pages | 22 |
| ISBN (Electronic) | 0936406232, 9780936406237 |
| DOIs | |
| State | Published - Jan 1 2019 |
| Externally published | Yes |
| Event | 32nd International Technical Meeting of the Satellite Division of the Institute of Navigation, ION GNSS+ 2019 - Miami, United States Duration: Sep 16 2019 → Sep 20 2019 |
Publication series
| Name | Proceedings of the 32nd International Technical Meeting of the Satellite Division of the Institute of Navigation, ION GNSS+ 2019 |
|---|
Conference
| Conference | 32nd International Technical Meeting of the Satellite Division of the Institute of Navigation, ION GNSS+ 2019 |
|---|---|
| Country | United States |
| City | Miami |
| Period | 9/16/19 → 9/20/19 |
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ASJC Scopus subject areas
- Communication
- Computer Science Applications
- Information Systems
- Software
- Electrical and Electronic Engineering
- Computer Networks and Communications
Cite this
Experimental integrity evaluation of tightly-integrated IMU/LIDAR including return-light intensity data. / Hassani, Ali; Morris, Nicholas; Spenko, Matthew; Joerger, Mathieu.
Proceedings of the 32nd International Technical Meeting of the Satellite Division of the Institute of Navigation, ION GNSS+ 2019. Institute of Navigation, 2019. p. 2637-2658 (Proceedings of the 32nd International Technical Meeting of the Satellite Division of the Institute of Navigation, ION GNSS+ 2019).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Experimental integrity evaluation of tightly-integrated IMU/LIDAR including return-light intensity data
AU - Hassani, Ali
AU - Morris, Nicholas
AU - Spenko, Matthew
AU - Joerger, Mathieu
PY - 2019/1/1
Y1 - 2019/1/1
N2 - This paper describes the design, analysis, and experimental evaluation of a new method to integrate measurements from light detection and ranging (LiDAR) and inertial measurement units (IMU). A tight IMU/LiDAR integration scheme is developed, which aims at exploiting the complementary properties of the two sensors while facilitating safety risk evaluation. In particular, the IMU is used to improve LiDAR position and orientation prediction (or pose), thereby reducing the the risk of incorrectly associating sensed features with mapped landmarks. Conversely, LiDAR pose estimation updates can limit the drift of IMU errors over time. In order to further improve data association, LiDAR return-light intensity measurements are incorporated, which helps distinguish landmarks and thus reduces the risk of incorrect associations. The new method is evaluated and analyzed using experimental data.
AB - This paper describes the design, analysis, and experimental evaluation of a new method to integrate measurements from light detection and ranging (LiDAR) and inertial measurement units (IMU). A tight IMU/LiDAR integration scheme is developed, which aims at exploiting the complementary properties of the two sensors while facilitating safety risk evaluation. In particular, the IMU is used to improve LiDAR position and orientation prediction (or pose), thereby reducing the the risk of incorrectly associating sensed features with mapped landmarks. Conversely, LiDAR pose estimation updates can limit the drift of IMU errors over time. In order to further improve data association, LiDAR return-light intensity measurements are incorporated, which helps distinguish landmarks and thus reduces the risk of incorrect associations. The new method is evaluated and analyzed using experimental data.
UR - http://www.scopus.com/inward/record.url?scp=85075266780&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85075266780&partnerID=8YFLogxK
U2 - 10.33012/2019.17095
DO - 10.33012/2019.17095
M3 - Conference contribution
AN - SCOPUS:85075266780
T3 - Proceedings of the 32nd International Technical Meeting of the Satellite Division of the Institute of Navigation, ION GNSS+ 2019
SP - 2637
EP - 2658
BT - Proceedings of the 32nd International Technical Meeting of the Satellite Division of the Institute of Navigation, ION GNSS+ 2019
PB - Institute of Navigation
ER -