Combined ASKF-EKF Framework for Topology Estimation

Part of the Springer Tracts in Advanced Robotics book series (STAR, volume 82)

Abstract

For surveying operations with a low-cost robot limited to a down-looking camera and a sonar altimeter, it is common practice to ensure that there is enough overlap between time-consecutive images as this is the only source of navigation data.When the robot revisits a previously surveyed area, it is essential to detect and match the non time-consecutive images to close a loop and, thus improve the trajectory estimate. While creating the mosaic, most of the existing algorithms try to match all image pairs to detect the non time-consecutive overlapping images when there is no additional navigation information.

In this chapter, a framework is presented to simultaneously obtain a 2D mosaic with the minimum number of image matching attempts and the best possible trajectory estimate. This is achieved by exploring the information contribution of the image matchings using a combination of augmented state and extended Kalman filter. Different strategies for choosing possible overlapping image pairs have been tested, and the results are given in different challenging underwater image sequences.

Keywords

Image Pair Image Centre Image Match Combine Strategy Time Epoch 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag GmbH Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Department of Mathematical EngineeringYildiz Technical UniversityIstanbulTurkey
  2. 2.Computer Vision and Robotics GroupUniversity of GironaGironaSpain

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