I. Dahm and J. Ziegler, "Adaptive methods to improve self-localization in robot soccer," in RoboCup Symposium, Fukuoka, 2002. Home/Search Document Details and Download
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Using Artificial Neural Networks to Construct a Meta-Model for .. - Dahm, Ziegler (2002) (2 citations) Self-citation (Dahm Ziegler) (Correct)
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I. Dahm and J. Ziegler, "Adaptive methods to improve self-localization in robot soccer," in RoboCup Symposium, Fukuoka, 2002.
A Fully Adaptive Signalspace Detector with Soft-Information.. - Dahm, Schmermbeck (2003) Self-citation (Dahm) (Correct)
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I. Dahm and J. Ziegler, "Adaptive methods to improve self-localization in robot soccer," in RoboCup Symposium Fukuoka, 2002.
RoboCup 2002 - Hans-Dieter Burkhard Uwe (2002) Self-citation (Dahm Ziegler) (Correct)
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Ingo Dahm and Jens Ziegler. Adaptive methods to improve self-localization in robot soccer. In RoboCup Symposium Fukuoka, 2002.
Using Artificial Neural Networks to Construct a Meta-Model for .. - Dahm, Ziegler (2002) (2 citations) Self-citation (Dahm Ziegler) (Correct)
.... 20, 44227 Dortmund, Germany, jens.ziegler uni dortmund.de Abstract Genetic programming[1] is expected to be a capable solution for designing fast and robust walking patterns for legged robots [2, 3, 4, 5] In fact, using this approach we have evolved very fast and stable patterns in the past [6]. The genetic programming approach is easy to implement since the fitness function here is given implicitly by the robots speed using a specific gait pattern. The best performing individual can be found easily by executing footraces. Unfortunately, such tournaments suffer from heavy wearout ....
....respectively. Since the distance between point and hyperplane is given by the dotproduct of the plane s normal vector and the point, an implementation of such a so called Signal Space Detector (SSD) 9, 10] is of low complexity. A hyperplane in the SSD can be estimated by a conventional perceptron [6, 11]. The so called weight vector of the perceptron is given by the hyperplanes normal vector. As discussed in [6, 12] the confidence of the decision of a SSD can be extracted using the distance to the decisive planes and by normalizing the weight vector depending on the observed data. The basic ....
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I. Dahm and J. Ziegler, "Adaptive methods to improve self-localization in robot soccer," in accepted for RoboCup Symposium, 2002.
GermanTeam 2002 - Düffert, Jüngel, Laue, Lötzsch.. (2002) (Correct)
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Dahm, I., Ziegler, J.: Adaptive Methods to Improve Self-Localization in Robot Soccer. In: RoboCup 2002. Lecture Notes in Artificial Intelligence. Springer (2003), to appear.
GermanTeam 2002 - Düffert, Jüngel, Laue, Lötzsch.. (2002) (Correct)
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Dahm, I., Ziegler, J.: Adaptive Methods to Improve Self-Localization in Robot Soccer. In: RoboCup 2002. Lecture Notes in Artificial Intelligence. Springer (2003), to appear.
GermanTeam 2002 - Düffert, Jüngel, Laue, Lötzsch.. (2002) (Correct)
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Dahm, I., Ziegler, J.: Adaptive Methods to Improve Self-Localization in Robot Soccer. In: RoboCup
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