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Contribution Details
| Type | Conference or Workshop Paper |
| Scope | Discipline-based scholarship |
| Published in Proceedings | Yes |
| Title | ICP stereo visual odometry for wheeled vehicles based on a 1DOF motion prior |
| Organization Unit | |
| Authors |
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| Presentation Type | paper |
| Item Subtype | Original Work |
| Refereed | Yes |
| Status | Published in final form |
| Language |
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| ISSN | 1050-4729 |
| Event Title | IEEE International Conference on Robotics and Automation (ICRA) |
| Event Type | conference |
| Event Location | Hong Kong |
| Event Start Date | May 31 - 2014 |
| Event End Date | June 7 - 2014 |
| Series Name | IEEE International Conference on Robotics and Automation. Proceedings |
| Place of Publication | Hong Kong |
| Publisher | Institute of Electrical and Electronics Engineers |
| Abstract Text | In this paper, we propose a novel, efficient stereo visual-odometry algorithm for ground vehicles moving in outdoor environments. To avoid the drawbacks of computationally-expensive outlier-removal steps based on random-sample schemes, we use a single-degree-of-freedom kinematic model of the vehicle to initialize an Iterative Closest Point (ICP) algorithm that is utilized to select high-quality inliers. The motion is then computed incrementally from the inliers using a standard linear 3D-to-2D pose-estimation method without any additional batch optimization. The performance of the approach is evaluated against state-of-the-art methods on both synthetic data and publicly-available datasets (e.g., KITTI and Devon Island) collected over several kilometers in both urban environments and challenging off-road terrains. Experiments show that the our algorithm outperforms state-of-the-art approaches in accuracy, runtime, and ease of implementation. |
| Related URLs |
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| Digital Object Identifier | 10.1109/ICRA.2014.6906914 |
| Other Identification Number | merlin-id:10215 |
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