Qualitative localization using omnidirectional images and invariant features

The present study proposes an innovative approach to qualitative mobile robot's localization using the concept of integral invariant on omnidirectional images. They are invariant depending on the image transformations caused by the movements of the robot. Several methods have been suggested to construct such invariants but they often rely on hypotheses about the transformation group which do not hold any more when dealing with omnidirectional sensors. These sensors benefit from an increasing interest in mobile robotics because of their field of view but they require adaptations of classical methods. This paper presents a method based on group averaging to construct invariant features which could be used to recognize a place with this type of sensors.

Authors

• Cyril Charron
• Ouiddad Labbani-Igbida
• El Mustapha Mouaddib

Keywords

• Mobile robots
• Robotics and automation
• Robot sensing systems
• Feature extraction
• Histograms
• Image recognition
• Layout
• Sensor phenomena and characterization
• Navigation
• Robot vision systems
• Invariant Features
• Omnidirectional Images
• Mobile Robot
• Image Transformation
• Robot Movement
• Histogram
• Distancing Measures
• Specific Methods
• Kernel Function
• Discrete Distribution
• Image Point
• Intrinsic Parameters
• Geometric Method
• Image Coordinates
• Reference Distribution
• Movement Amplitude
• Grid Nodes
• Eigenspace
• Color Bands
• Sensor Geometry
• Center Of The Room
• Color Histogram
• Localization
• Omnidirectional
• Invariants