Abstract
A neuro-evolutive system for mobile robot ego-motion estimation using time-of-flight (TOF) 3D camera readings is presented in this paper. It is composed of two modules. First, a Neural Gas adaptative algorithm is used to obtain a set of codevectors quantizing the preprocessed 3D measurements provided by the camera. Second, codevector sets from consecutive frames are matched using an evolutive algorithm in order to estimate the motion of the robot between those two positions. © 2009 Springer Berlin Heidelberg.
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CITATION STYLE
Villaverde, I., Echegoyen, Z., & Graña, M. (2009). Neuro-evolutive system for ego-motion estimation with a 3D Camera. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5506 LNCS, pp. 1021–1028). https://doi.org/10.1007/978-3-642-02490-0_124
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