Abstract
Human motion recognition systems play an important role in improving the ability of robots to support human life. This paper proposes a novel motion recognition method based on haptic data (i.e., position and force information). First, haptic data are obtained using a bilateral control system. Second, the haptic data are divided into action components, using modal transformation. Finally, both the position and the force information in each action component are compared with recorded data. A dynamic programming pattern-matching algorithm is used to recognize the desired motion, and the validity of the proposed method is verified experimentally. In the experiments, the proposed method is applied to a grasping motion. The proposed method can trigger scaled bilateral control and assist the operator in real time.
| Original language | English |
|---|---|
| Article number | 6376180 |
| Pages (from-to) | 2043-2051 |
| Number of pages | 9 |
| Journal | IEEE Transactions on Industrial Informatics |
| Volume | 9 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 2013 |
Fingerprint
Keywords
- Bilateral control
- Dynamic programming
- Force sensation
- Haptics
- Master-slave robot system
- Motion recognition
ASJC Scopus subject areas
- Electrical and Electronic Engineering
- Control and Systems Engineering
- Computer Science Applications
- Information Systems
Cite this
Recognition of grasping motion based on modal space haptic information using DP pattern-matching algorithm. / Nozaki, Takahiro; Mizoguchi, Takahiro; Saito, Yuki; Yashiro, Daisuke; Ohnishi, Kouhei.
In: IEEE Transactions on Industrial Informatics, Vol. 9, No. 4, 6376180, 2013, p. 2043-2051.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Recognition of grasping motion based on modal space haptic information using DP pattern-matching algorithm
AU - Nozaki, Takahiro
AU - Mizoguchi, Takahiro
AU - Saito, Yuki
AU - Yashiro, Daisuke
AU - Ohnishi, Kouhei
PY - 2013
Y1 - 2013
N2 - Human motion recognition systems play an important role in improving the ability of robots to support human life. This paper proposes a novel motion recognition method based on haptic data (i.e., position and force information). First, haptic data are obtained using a bilateral control system. Second, the haptic data are divided into action components, using modal transformation. Finally, both the position and the force information in each action component are compared with recorded data. A dynamic programming pattern-matching algorithm is used to recognize the desired motion, and the validity of the proposed method is verified experimentally. In the experiments, the proposed method is applied to a grasping motion. The proposed method can trigger scaled bilateral control and assist the operator in real time.
AB - Human motion recognition systems play an important role in improving the ability of robots to support human life. This paper proposes a novel motion recognition method based on haptic data (i.e., position and force information). First, haptic data are obtained using a bilateral control system. Second, the haptic data are divided into action components, using modal transformation. Finally, both the position and the force information in each action component are compared with recorded data. A dynamic programming pattern-matching algorithm is used to recognize the desired motion, and the validity of the proposed method is verified experimentally. In the experiments, the proposed method is applied to a grasping motion. The proposed method can trigger scaled bilateral control and assist the operator in real time.
KW - Bilateral control
KW - Dynamic programming
KW - Force sensation
KW - Haptics
KW - Master-slave robot system
KW - Motion recognition
UR - http://www.scopus.com/inward/record.url?scp=84886709859&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84886709859&partnerID=8YFLogxK
U2 - 10.1109/TII.2012.2232934
DO - 10.1109/TII.2012.2232934
M3 - Article
AN - SCOPUS:84886709859
VL - 9
SP - 2043
EP - 2051
JO - IEEE Transactions on Industrial Informatics
JF - IEEE Transactions on Industrial Informatics
SN - 1551-3203
IS - 4
M1 - 6376180
ER -