Visual homing in environments with anisotropic landmark distribution
Autonomous Robots
An Insect-Inspired Active Vision Approach for Orientation Estimation with Panoramic Images
IWINAC '07 Proceedings of the 2nd international work-conference on The Interplay Between Natural and Artificial Computation, Part I: Bio-inspired Modeling of Cognitive Tasks
Linked Local Visual Navigation and Robustness to Motor Noise and Route Displacement
SAB '08 Proceedings of the 10th international conference on Simulation of Adaptive Behavior: From Animals to Animats
Local visual homing by warping of two-dimensional images
Robotics and Autonomous Systems
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Three 2D-warping schemes for visual robot navigation
Autonomous Robots
Slicing the view: occlusion-aware view-based robot navigation
Proceedings of the 32nd DAGM conference on Pattern recognition
Landmark vectors with quantized distance information for homing navigation
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
Image-based homing navigation with landmark arrangement matching
Information Sciences: an International Journal
An insect-inspired, decentralized memory for robot navigation
ICIRA'11 Proceedings of the 4th international conference on Intelligent Robotics and Applications - Volume Part II
Analyzing the effect of landmark vectors in homing navigation
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
How active vision facilitates familiarity-based homing
Living Machines'13 Proceedings of the Second international conference on Biomimetic and Biohybrid Systems
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In natural images, the distance measure between two images taken at different locations rises smoothly with increasing distance between the locations. This fact can be exploited for local visual homing where the task is to reach a goal location that is characterized by a snapshot image: descending in the image distance will lead the agent to the goal location. To compute an estimate of the spatial gradient in the distance measure, its value must be sampled at three noncollinear points. An animal or robot would have to insert exploratory movements into its home trajectory to collect these samples. Here we suggest a method based on the matched-filter concept that allows one to estimate the gradient without exploratory movements. Two matched filters – optical flow fields resulting from translatory movements in the horizontal plane – are used to predict two images in perpendicular directions from the current location. We investigate the relation to differential flow methods applied to the local homing problem and show that the matched-filter approach produces reliable homing behavior on image databases. Two alternative methods that only require a single matched filter are suggested. The matched-filter concept is also applied to derive a home-vector equation for a Fourier-based parameter method.