A mobile robot that learns its place
Neural Computation
Insect-inspired robotic homing
Adaptive Behavior
Vision for Mobile Robot Navigation: A Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
Neural Network Perception for Mobile Robot Guidance
Neural Network Perception for Mobile Robot Guidance
Comparing Images Using the Hausdorff Distance
IEEE Transactions on Pattern Analysis and Machine Intelligence
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Autonomous mobile robot navigation systems are based on three principal kinds of techniques: map-based navigation, map-building-based navigation and mapless navigation. We propose a mapless method for trajectory description in unknown indoor environments. The method uses distance measurements from a 2D laser range finder, digitises the robot's visibility area, eliminates superfluous data and reorients their presentation with laws similar to those used in cellular automata. The landmarks are extracted and organised in a panoramic description called fresco. The frescoes which are validated by means of neighbourhood rules. The most informative frescoes are detected by means of two criteria and stored. The stored frescoes are considered as a human-like descritption of the robot's route and could be used by the robot to retrieve its route to its starting point.