6 Result(s)
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Article
Motion codeword generation using selective subsequence clustering for human action recognition
The understanding of human activity is one of the key research areas in human-centered robotic applications. In this paper, we propose complexity-based motion features for recognizing human actions. Using a ti...
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Article
Modeling and evaluating Gaussian mixture model based on motion granularity
To model manipulation tasks, we propose a novel method for learning manipulation skills based on the degree of motion granularity. Even though manipulation tasks usually consist of a mixture of fine-grained an...
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Chapter
Motion-Based Learning
In this Chapter, we introduce several learning approaches to generate non-preprogrammed motions for a virtual human. Motion primitives and their causalities should first be learned from a task, which consists ...
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Article
Autonomous framework for segmenting robot trajectories of manipulation task
In manipulation tasks, motion trajectories are characterized by a set of key phases (i.e., motion primitives). It is therefore important to learn the motion primitives embedded in such tasks from a complete de...
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Chapter and Conference Paper
Skill Learning and Inference Framework
We propose a skill learning and inference framework, which includes five processing modules as follows: 1) human demonstration process, 2) autonomous segmentation process, 3) process of learning dynamic moveme...
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Chapter and Conference Paper
Learning of Subgoals for Goal-Oriented Behavior Control of Mobile Robots
Subgoal learning is investigated to effectively build a goal-oriented behavior control rule with which a mobile robot can achieve a task goal for any starting task configurations. For this, states of interest ...
