Robust vision-based localization by combining an image-retrieval system with Monte Carlo localization

By Jürgen Wolf, Wolfram Burgard, Hans Burkhardt. 2005

267 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Computer Vision and Pattern Recognition

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In Aerospace Engineering

In Computer Vision and Pattern Recognition

Citations in the corpus

Filtering with State-Observation Examples via Kernel Monte Carlo Filter (2013, methodology): “s is also implied by the experiments in the next subsection. 6.3 Vision-based mobile robot localization We applied KMCF to the problem of vision-based mobile robot localization (Vlassis et al., 2002; Wolf et al., 2005; Quigley et al., 2010). We consider a robot moving in a building. The robot takes ”
Non-commercial Research and Educational Use including without Limitation Use in Instruction at Your Institution, Sending It to Specific Colleagues That You Know, and Providing a Copy to Your Institution's Administrator. All Other Uses, Reproduction and Distribution, including without Limitation Comm (2005, unknown): “From these couplings accurate relative solute geometries and information about solute conformational change can be obtained.”
Sub-meter indoor localization in unmodified environments with inexpensive sensors (2010, methodology): “Several papers have utilized MCL with cameras including [10], [11], [12], [13], [14].”
Fast and Incremental Method for Loop-Closure Detection Using Bags of Visual Words (2008, methodology): “Although successfully adapted to vision [13], this method does not match our requirements since it relies on the existence of a map obtained beforehand.”
A Theoretical Foundation of Network Localization and Navigation (2018, background): “Typical examples include angular velocities and accelerations of a node obtained by inertial measurement units (IMUs) [76]–[81], or feature points in images captured by vision sensors [82]–[85].”
FAB-MAP: Probabilistic Localization and Mapping in the Space of Appearance (2008, methodology): “More recently, Wolf et al. (2005) used an image retrieval system based on invariant features as the basis of a Monte Carlo localization scheme.”