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Appearance-based mapping and localisation using feature stability histograms

Appearance-based mapping and localisation using feature stability histograms

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© The Institution of Engineering and Technology
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Proposed is an appearance-based mapping and localisation method based on the human memory model, which is used to build a feature stability histogram (FSH) at each node in the robot topological map. FSH registers local feature stability over time through a voting scheme, and most stable features are considered for mapping and Bayesian localisation. Experimental results are presented using omnidirectional images acquired through long-term acquisition considering: illumination changes, occlusions, random removal of features and perceptual aliasing. This method is able to adapt the internal node's representation through time to achieve global and local robot localisation.

Inspec keywords: stability; path planning; Bayes methods; SLAM (robots); mobile robots; robot vision

Other keywords: human memory model; feature stability histograms; appearance based mapping; voting scheme; robot topological map; omnidirectional images; localisation; Bayesian localisation

Subjects: Other topics in statistics; Stability in control theory; Spatial variables control; Mobile robots; Computer vision and image processing techniques

References

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      • Dayoub, F., Duckett, T.: `An adaptive appearance-based map for long-term topological localisation of mobile robots', IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, Nice, France, 2008, p. 3364–3369.
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