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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Junghyun Kwon Park, F.C. |
| Copyright Year | 1996 |
| Abstract | Recent studies have shown that the perception of natural movements - in the sense of being "humanlike" - depends on both joint and task space characteristics of the movement. This paper proposes a movement generation framework that merges two established techniques from gesture recognition and motion generation - hidden Markov models (HMMs) and principal components - into an efficient and reliable means of generating natural movements, which uniformly considers joint and task space characteristics. Given human motion data that are classified into several movement categories, for each category, the principal components extracted from the joint trajectories are used as basis elements. An HMM is, in turn, designed and trained for each movement class using the human task space motion data. Natural movements are generated as the optimal linear combination of principal components, which yields the highest probability for the trained HMM. Experimental case studies with a prototype humanoid robot demonstrate the various advantages of our proposed framework. |
| Page Count | 11 |
| File Size | 1316300 |
| Starting Page | 1184 |
| Ending Page | 1194 |
| File Format | |
| ISSN | 10834419 |
| Volume Number | 38 |
| Issue Number | 5 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2008-10-01 |
| Publisher Place | U.S.A. |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Hidden Markov models Humanoid robots Human robot interaction Character generation Databases Torque Intelligent robots Aerospace materials Acceleration Character recognition principal component Hidden Markov model (HMM) movement primitive natural movement |
| Content Type | Text |
| Resource Type | Article |
| Subject | Control and Systems Engineering Information Systems Electrical and Electronic Engineering Human-Computer Interaction Computer Science Applications Software |
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