Abstract
A novel inverse kinematics solution based on the back propagation neural network (NN) for redundant manipulators is developed for online obstacles avoidance. A laser transducer at the end-effctor is used for online planning the trajectory. Since the inverse kinematics in the present problem has infinite number of joint angle vectors, a fuzzy reasoning system is designed to generate an approximate value for that vector. This vector is fed into the NN as a hint input vector rather than as a training vector to guide the output of the NN. Simulations are implemented on both three- and four-link redundant planar manipulators to show the effectiveness of the proposed position control system.
| Original language | English |
|---|---|
| Pages (from-to) | 17-29 |
| Number of pages | 13 |
| Journal | International Journal of Control, Automation and Systems |
| Volume | 4 |
| Issue number | 1 |
| Publication status | Published - Feb 2006 |
| Externally published | Yes |
Fingerprint
Keywords
- Fuzzy system
- Inverse kinematics
- Neural networks
- Online collision avoidance
- Redundant manipulators
ASJC Scopus subject areas
- Control and Systems Engineering
Cite this
Fuzzy hint acquisition for the collision avoidance solution of redundant manipulators using neural network. / Assal, Samy F M; Watanabe, Keigo; Izumi, Kiyotaka.
In: International Journal of Control, Automation and Systems, Vol. 4, No. 1, 02.2006, p. 17-29.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Fuzzy hint acquisition for the collision avoidance solution of redundant manipulators using neural network
AU - Assal, Samy F M
AU - Watanabe, Keigo
AU - Izumi, Kiyotaka
PY - 2006/2
Y1 - 2006/2
N2 - A novel inverse kinematics solution based on the back propagation neural network (NN) for redundant manipulators is developed for online obstacles avoidance. A laser transducer at the end-effctor is used for online planning the trajectory. Since the inverse kinematics in the present problem has infinite number of joint angle vectors, a fuzzy reasoning system is designed to generate an approximate value for that vector. This vector is fed into the NN as a hint input vector rather than as a training vector to guide the output of the NN. Simulations are implemented on both three- and four-link redundant planar manipulators to show the effectiveness of the proposed position control system.
AB - A novel inverse kinematics solution based on the back propagation neural network (NN) for redundant manipulators is developed for online obstacles avoidance. A laser transducer at the end-effctor is used for online planning the trajectory. Since the inverse kinematics in the present problem has infinite number of joint angle vectors, a fuzzy reasoning system is designed to generate an approximate value for that vector. This vector is fed into the NN as a hint input vector rather than as a training vector to guide the output of the NN. Simulations are implemented on both three- and four-link redundant planar manipulators to show the effectiveness of the proposed position control system.
KW - Fuzzy system
KW - Inverse kinematics
KW - Neural networks
KW - Online collision avoidance
KW - Redundant manipulators
UR - http://www.scopus.com/inward/record.url?scp=31944446444&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=31944446444&partnerID=8YFLogxK
M3 - Article
AN - SCOPUS:31944446444
VL - 4
SP - 17
EP - 29
JO - International Journal of Control, Automation and Systems
JF - International Journal of Control, Automation and Systems
SN - 1598-6446
IS - 1
ER -