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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | McManus, C. Furgale, P. Stenning, B. Barfoot, T.D. |
| Copyright Year | 2012 |
| Description | Author affiliation: Autonomous Space Robotics Lab, University of Toronto Institute for Aerospace Studies, Canada (Stenning, B.; Barfoot, T.D.) || Mobile Robotics Group, University of Oxford, England (McManus, C.) || Autonomous Systems Lab, ETH Zürich, Switzerland (Furgale, P.) |
| Abstract | Visual Teach and Repeat (VT&R) has proven to be an effective method to allow a vehicle to autonomously repeat any previously driven route without the need for a global positioning system. One of the major challenges for a method that relies on visual input to recognize previously visited places is lighting change, as this can make the appearance of a scene look drastically different. For this reason, passive sensors, such as cameras, are not ideal for outdoor environments with inconsistent/inadequate light. However, camera-based systems have been very successful for localization and mapping in outdoor, unstructured terrain, which can be largely attributed to the use of sparse, appearance-based computer vision techniques. Thus, in an effort to achieve lighting invariance and to continue to exploit the heritage of the appearance-based vision techniques traditionally used with cameras, this paper presents the first VT&R system that uses appearance-based techniques with laser scanners for motion estimation. The system has been field tested in a planetary analogue environment for an entire diurnal cycle, covering more than 11km with an autonomy rate of 99.7% of the distance traveled. |
| Starting Page | 389 |
| Ending Page | 396 |
| File Size | 1966802 |
| Page Count | 8 |
| File Format | |
| ISBN | 9781467314039 |
| ISSN | 10504729 |
| e-ISBN | 9781467314053 |
| e-ISBN | 9781467314046 |
| DOI | 10.1109/ICRA.2012.6224654 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-05-14 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Robots Navigation Image edge detection Vehicles Cameras Calibration Manuals |
| Content Type | Text |
| Resource Type | Article |
| Subject | Artificial Intelligence Control and Systems Engineering Electrical and Electronic Engineering Software |
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