Synthesis of New Dynamic Movement Primitives Through Search in a Hierarchical Database of Example Movements. (6th October 2015)

• Record Type: Journal Article
• Authors: Deniša, Miha; Ude, Aleš
• Is Part Of: International journal of advanced robotic systems. Volume 12:Number 10(2015)
• Publication Date: 2015-10-06
• Subjects: Imitation Learning -- Motor Primitives -- Trajectory Databases -- Hierarchical Graph Search; Robotics -- Periodicals; Robotics; Periodicals; 629.892
• DOI: 10.5772/61036
• Languages: English
• ISSNs: 1729-8806

Abstract

This paper presents a novel approach to discovering motor primitives in a hierarchical database of example trajectories. An initial set of example trajectories is obtained by human demonstration. The trajectories are clustered and organized in a binary tree-like hierarchical structure, from which transition graphs at different levels of granularity are constructed. A novel procedure for searching in this hierarchical structure is presented. It can exploit the interdependencies between movements and can discover new series of partial paths. From these partial paths, complete new movements are generated by encoding them as dynamic movement primitives. In this way, the number of example trajectories that must be acquired with the assistance of a human teacher can be reduced. By combining the results of the hierarchical search with statistical generalization techniques, a complete representation of new, not directly demonstrated, movement primitives can be generated.