Sinc-Based Dynamic Movement Primitives for Encoding Point-to-point Kinematic Behaviors

This work proposes the utilization of sinc functions as kernels of Dynamic Movement Primitives (DMP) models for encoding point-to-point kinematic behaviors. The proposed method presents a number of advantages with respect to the state of the art, as it (i) involves a simple learning technique, (ii)...

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Bibliographic Details
Published in2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) pp. 8339 - 8345
Main Authors Papageorgiou, Dimitrios, Sidiropoulos, Antonis, Doulgeri, Zoe
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2018
Subjects
Biological system modeling
Complexity theory
Computational modeling
Encoding
Frequency modulation
Kinematics
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Summary:This work proposes the utilization of sinc functions as kernels of Dynamic Movement Primitives (DMP) models for encoding point-to-point kinematic behaviors. The proposed method presents a number of advantages with respect to the state of the art, as it (i) involves a simple learning technique, (ii) provides a method to determine the minimum required number of basis functions, based on the frequency content of the demonstrated motion and (iii) provides the ability to pre-define the reproduction accuracy of the learned behavior. The ability of the proposed model to accurately reproduce the behavior is demonstrated through simulations and experiments. Comparisons with the Gaussian-based DMP model show the proposed method's superiority in terms of computational complexity of learning and accuracy for a specific number of kernels.
ISSN:2153-0866
DOI:10.1109/IROS.2018.8594479