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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Krishnaswamy, K. Susca, S. McCroskey, R. Seiler, P. Lukas, J. Kotaba, O. Bageshwar, V. Ganguli, S. |
| Copyright Year | 2008 |
| Description | Author affiliation: Honeywell Adv. Technol., Minneapolis, MN (Krishnaswamy, K.; Susca, S.; McCroskey, R.; Seiler, P.; Bageshwar, V.; Ganguli, S.) |
| Abstract | We present technologies that are being developed to address the need for a navigation solution in the absence of Global Navigation Satellite Systems (GNSS) measurements. The navigation system uses sensors such as vision systems, RADARS and LIDARS with feature extraction, matching and motion estimation algorithms. We present experimental results of using scale invariant feature transform, speeded up robust features, and modified Harris feature extraction algorithms and compare the performance. We also present methods to extract lines and planes that can aid in navigation. For motion estimation we present results for visual odometry as well as simultaneous localization and mapping navigation. We experimentally verify the algorithms in both a realtime Linux framework as well as offline. We also present ongoing work in vision integrated navigation in an attitude and heading reference system as well as an extended Kalman filter framework. All the methods we present in this paper are incremental navigation methods. |
| Starting Page | 541 |
| Ending Page | 551 |
| File Size | 841483 |
| Page Count | 11 |
| File Format | |
| ISBN | 9781424415366 |
| DOI | 10.1109/PLANS.2008.4570062 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2008-05-05 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Sensor fusion Satellite navigation systems Feature extraction Motion estimation Global Positioning System Sensor systems Machine vision Spaceborne radar Laser radar Robustness |
| Content Type | Text |
| Resource Type | Article |
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