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 1 2006 |
| Externally published | Yes |
Keywords
- Fuzzy system
- Inverse kinematics
- Neural networks
- Online collision avoidance
- Redundant manipulators
ASJC Scopus subject areas
- Control and Systems Engineering
- Computer Science Applications
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Assal, S. F. M., Watanabe, K., & Izumi, K. (2006). Fuzzy hint acquisition for the collision avoidance solution of redundant manipulators using neural network. International Journal of Control, Automation and Systems, 4(1), 17-29.