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Data Mining Applications in Robotics Engineering

Data Mining Applications in Robotics Engineering. Blink Sakulkueakulsuk. References. D. Wilking , and T. Rofer , Realtime Object Recognition Using Decision Tree Learning, 2005 http :// www.informatik.uni-bremen.de/kogrob/papers/rc05-objectrecognition.pd

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Data Mining Applications in Robotics Engineering

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  1. Data Mining Applicationsin Robotics Engineering Blink Sakulkueakulsuk

  2. References • D. Wilking, and T. Rofer, Realtime Object Recognition Using Decision Tree Learning, 2005 http://www.informatik.uni-bremen.de/kogrob/papers/rc05-objectrecognition.pd • J. Li, Q. Pan, and B. Hong, A New Approach of Multi-robot Cooperative Pursuit Based on Association Rule Data Mining, 2009 http://cdn.intechopen.com/pdfs-wm/6967.pdf • A. Ravankar, Y. Hoshino, T. Emaru, and Y. Kobayashi, Robot Mapping Using k-means Clustering Of Laser Range Sensor Data, 2012 http://bncss.org/index.php/bncss/article/view/2/2 • H. Lipson, Mining experimental data for dynamical invariants - from cognitive robotics to computational biology, 2010 http://videolectures.net/ecmlpkdd2010_lipson_med/

  3. What is Robotics Engineering? • Interdisciplinary Field • RBE = ME + EE + CS • Computer Science components • Computer Vision • Artificial Intelligence • Machine Learning • DATA MINING!!!

  4. DM: Decision Trees • Realtime Object Recognition Using Decision Tree Learning From Ref.1 page 2

  5. From Ref.1 page 3

  6. DM: Clustering • Robot Mapping Using k-means Clustering Of Laser Range Sensor Data • Create a map of the environment From Ref.3 page 2

  7. From Ref.3 page 2-3

  8. Clustering Limitations • Not good with noise. From Ref.3 page 3

  9. Other DM Applications • Association Rules • Multi-robot Cooperative Pursuit Based on Association Rule Data Mining • The robots try to pursuit a target. Using association rules, the robots form a group. • Other applications • Mining experimental data for dynamical invariants - from cognitive robotics to computational biology • Invariants = Something that is constant in the system • Finding invariants = using unsupervised learning to find patterns

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