Browsing by Author "Chan, Hoa-Yu"

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Intention deduction from demonstrated trajectory for tool-handling task
(2013)
Chan, Hoa-Yu
;
Young, Kuu-young
;
Fu, Hsin-Chia
;
資訊工程學系
;
電子工程學系及電子研究所
When the robot comes to a home-like environment, its programming becomes very demanding. The concept of learning by demonstration is thus introduced, which may remove the load of detailed analysis and programming from the user. Following this concept, in this article, we propose a novel approach for the robot to deduce the intention of the demonstrator from the trajectories during task execution. We focus on the tool-handling task, which is common in the home environment, but complicated for analysis. The proposed approach does not pre-define-motions or put constraints on motion speed, while allowing the event order to be altered and allowing for the presence of redundant operations during the demonstration. We apply the concept of cross-validation to locate the portions of the trajectory that correspond to delicate and skillful maneuvering, and apply an algorithm based on dynamic programming previously developed to search for the most probable intention. In experiments, we applied the proposed approach for two different kinds of tasks, the pouring and coffee-making tasks, with the number of objects and their locations varied during demonstrations. To further investigate our method's scalability and generality, we also performed intensive analysis on the parameters involved in the tasks.
Intention Learning From Human Demonstration
(2011-05-01)
Chan, Hoa-Yu
;
Young, Kuu-Young
;
Fu, Hsin-Chia
;
資訊工程學系
;
電機工程學系
Equipped with better sensing and learning capabilities, robots nowadays are meant to perform versatile tasks. To remove the load of detailed analysis and programming from the engineer, a concept has been proposed that the robot may learn how to execute the task from human demonstration by itself Following the idea, in this paper, we propose an approach for the robot to learn the intention of the demonstrator from the resultant trajectory during task execution. The proposed approach, identifies the portions of the trajectory that correspond to delicate and skillful maneuvering. Those portions, referred to as motion features, may implicate the intention of the demonstrator. As the trajectory may result from so many possible intentions, it poses a severe challenge on finding the correct one's. We first formulate the problem into a realizable mathematical form and then employ the method of dynamic programming for the search. Experiments based on the pouring and also fruit jam tasks are performed to demonstrate the proposed approach, in which the derived intention is used to execute the same task under different experimental settings.