An adaptive communication protocol for cooperating mobile robots
Proceedings of the second international conference on From animals to animats 2 : simulation of adaptive behavior: simulation of adaptive behavior
Topological mapping for mobile robots using a combination of sonar and vision sensing
AAAI'94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 2)
Bayesian Landmark Learning for Mobile Robot Localization
Machine Learning
Neural Networks - Special issue on organisation of computation in brain-like systems
Spatial learning for navigation in dynamic environments
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Exploration of configural representation in landmark learning using working memory toolkit
Pattern Recognition Letters
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Selecting landmarks for use by a navigating mobile robot is important for map-building systems. However, it can also provide a way by which robots can communicate route information, so that one robot can tell another how to find a goal location. A route through an environment can be described by the landmarks encountered along the path, and a robot following the same path must identify the perceptions corresponding to the actual landmarks in the description in order to localise itself. This paper presents an algorithm to automatically select landmarks, choosing as landmarks places that do not fit into a model of typical perceptions acquired by the robot. Four methods of aligning the landmarks between different runs on the same route are also presented. The different alignment methods are evaluated according to both how well they produce matching landmarks and how suitable such alignment methods would be for use in a route communication system.