Vision-based Frozen Surface Egress: A Docking Algorithm for the ENDURANCE
This paper presents a vision-based docking algorithm for an autonomous underwater vehicle (AUV). The algorithm allows the AUV to egress through a melthole in the frozen surface of a lake after the AUV’s dead-reckoning system brings the vehicle in the vicinity of the melthole. A blinking light source...
| Main Authors: | , , , , , |
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| Other Authors: | |
| Format: | Text |
| Language: | English |
| Subjects: | |
| Online Access: | http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.188.711 http://www.cs.utexas.edu/%7Eshilpa/publications/2009/murarka-uust-09.pdf |
| Summary: | This paper presents a vision-based docking algorithm for an autonomous underwater vehicle (AUV). The algorithm allows the AUV to egress through a melthole in the frozen surface of a lake after the AUV’s dead-reckoning system brings the vehicle in the vicinity of the melthole. A blinking light source is used to guide the robot towards the melthole and through it. A light detection and tracking algorithm performs a temporal analysis of images captured from an upward-facing camera to detect sources of illumination and identify and track the blinking target light source. The vehicle first moves in a spiral pattern to search for the target using the light-detection algorithm. On finding the light, the AUV ascends while keeping the light centered in the camera’s field of view. The vision-based docking algorithm was implemented on the ENDURANCE AUV and tested during a four-week-long scientific mission to explore West Lake Bonney in Antarctica in December 2008. The algorithm was used to ascend in 10 missions and to descend in 8 missions through a three-meter-deep melthole only slightly larger than the vehicle itself. In each instance, the vehicle was able to safely ascend or descend without coming into contact with the walls. Quantitative analysis of mission data confirmed that the tracking algorithm and ascent controller were robust and precise. 1 |
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