A Novel Trajectory Generation Method for Robot Control

Authors:
Kejun Ning;Tomas Kulvicius;Minija Tamosiunaite;Florentin Wörgötter
Affiliations:
Bernstein Center for Computational Neuroscience, Inst. of Physics III, University of Göttingen, Göttingen, Germany 37077 and Research & Technology, Lenovo, Beijing, China 100085;Bernstein Center for Computational Neuroscience, Inst. of Physics III, University of Göttingen, Göttingen, Germany 37077;Bernstein Center for Computational Neuroscience, Inst. of Physics III, University of Göttingen, Göttingen, Germany 37077;Bernstein Center for Computational Neuroscience, Inst. of Physics III, University of Göttingen, Göttingen, Germany 37077
Venue:
Journal of Intelligent and Robotic Systems
Year:
2012

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Abstract

This paper presents a novel trajectory generator based on Dynamic Movement Primitives (DMP). The key ideas from the original DMP formalism are extracted, reformulated and extended from a control theoretical viewpoint. This method can generate smooth trajectories, satisfy position- and velocity boundary conditions at start- and endpoint with high precision, and follow accurately geometrical paths as desired. Paths can be complex and processed as a whole, and smooth transitions can be generated automatically. Performance is analyzed for several cases and a comparison with a spline-based trajectory generation method is provided. Results are comparable and, thus, this novel trajectory generating technology appears to be a viable alternative to the existing solutions not only for service robotics but possibly also in industry.