C4.5: programs for machine learning
C4.5: programs for machine learning
IEEE Transactions on Pattern Analysis and Machine Intelligence
An appraisal of a decision tree approach to image classification
IJCAI'83 Proceedings of the Eighth international joint conference on Artificial intelligence - Volume 1
Integrating Simple Unreliable Perceptions for Accurate Robot Modeling in the Four-Legged League
RoboCup 2006: Robot Soccer World Cup X
Automatic Adaptation and Analysis of SIP Headers Using Decision Trees
Principles, Systems and Applications of IP Telecommunications. Services and Security for Next Generation Networks
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Neural robot detection in robocup
Biomimetic Neural Learning for Intelligent Robots
Learning visual obstacle detection using color histogram features
Robot Soccer World Cup XV
Benchmarks for robotic soccer vision
Robot Soccer World Cup XV
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An object recognition process in general is designed as a domain specific, highly specialized task. As the complexity of such a process tends to be rather inestimable, machine learning is used to achieve better results in recognition. The goal of the process presented in this paper is the computation of the pose of a visible robot, i. e. the distance, angle, and orientation. The recognition process itself, the division into subtasks, as well as the results of the process are presented. The algorithms involved have been implemented and tested on a Sony Aibo.