Acquisition of a symbolic manipulation task model by attention point analysis

Authors: Ogawara K.; Takamatsu J.; Kimura H.; Ikeuchi K.

Source: Advanced Robotics, Volume 17, Number 10, 2003 , pp. 1073-1091(19)

Publisher: VSP, an imprint of Brill

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Abstract:

As a way of automatic programming of robot behavior, a method for building a symbolic manipulation task model from a demonstration is proposed. The feature of this model is that it explicitly stores the information about the essential parts of a task, i.e. interaction between a hand and an environmental object, or interaction between a grasped object and a target object. Thus, even in different environments, this method reproduces robot motion as similar as possible to that of humans to complete the task while changing the motion during non-essential parts to adapt to the current environment. To automatically determine the essential parts, a method called attention point analysis is proposed; this method searches for the nature of a task using multiple sensors and estimates the parameters to represent the task. A humanoid robot is used to verify the reproduced robot motion based on the generated task model.

Keywords: MAN-MACHINE INTERFACES; TEACHING; LEARNING SYSTEMS; INTELLIGENT ROBOTS; HUMANOID ROBOTS

Document Type: Research article

DOI: 10.1163/156855303322554436

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