Paper
2 May 2007 Precise visual navigation using multi-stereo vision and landmark matching
Zhiwei Zhu, Taragay Oskiper, Supun Samarasekera, Rakesh Kumar
Author Affiliations +
Abstract
Traditional vision-based navigation system often drifts over time during navigation. In this paper, we propose a set of techniques which greatly reduce the long term drift and also improve its robustness to many failure conditions. In our approach, two pairs of stereo cameras are integrated to form a forward/backward multi-stereo camera system. As a result, the Field-Of-View of the system is extended significantly to capture more natural landmarks from the scene. This helps to increase the pose estimation accuracy as well as reduce the failure situations. Secondly, a global landmark matching technique is used to recognize the previously visited locations during navigation. Using the matched landmarks, a pose correction technique is used to eliminate the accumulated navigation drift. Finally, in order to further improve the robustness of the system, measurements from low-cost Inertial Measurement Unit (IMU) and Global Positioning System (GPS) sensors are integrated with the visual odometry in an extended Kalman Filtering framework. Our system is significantly more accurate and robust than previously published techniques (1∼5% localization error) over long-distance navigation both indoors and outdoors. Real world experiments on a human worn system show that the location can be estimated within 1 meter over 500 meters (around 0.1% localization error averagely) without the use of GPS information.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Zhiwei Zhu, Taragay Oskiper, Supun Samarasekera, and Rakesh Kumar "Precise visual navigation using multi-stereo vision and landmark matching", Proc. SPIE 6561, Unmanned Systems Technology IX, 656108 (2 May 2007); https://doi.org/10.1117/12.719810
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Visualization

Cameras

Databases

Global Positioning System

Navigation systems

Sensors

Imaging systems

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