Abstract
Forward kinematics (FK) mapping for parallel mechanisms is difficult as it involves highly coupled nonlinear motions. Since FK is a key element in closed loop position and force control of parallel manipulators, an accurate prediction of end pose from the available link lengths is essential. This paper proposes a modified Sugeno Inference System (SIS) to accurately predict the forward mapping between joint and Cartesian coordinates. The SIS algorithm has been implemented on a new parallel robotic device, designed for flexible ankle rehabilitation treatments. To increase the accuracy of the SIS, antecedent fuzzy variables are tuned using a modified genetic algorithm and consequent crisp membership functions are trained with a gradient descent algorithm. It has been found that the proposed system provides better accuracy and is also time efficient, which makes it a better candidate for real time control applications.
| Original language | English |
|---|---|
| Title of host publication | 39th International Symposium on Robotics, ISR 2008 |
| Pages | 236-241 |
| Number of pages | 6 |
| Publication status | Published - 2008 |
| Externally published | Yes |
| Event | 39th International Symposium on Robotics, ISR 2008 - Seoul, Korea, Republic of Duration: Oct 15 2008 → Oct 17 2008 |
Other
| Other | 39th International Symposium on Robotics, ISR 2008 |
|---|---|
| Country | Korea, Republic of |
| City | Seoul |
| Period | 10/15/08 → 10/17/08 |
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ASJC Scopus subject areas
- Artificial Intelligence
- Human-Computer Interaction
- Software
Cite this
Forward kinematic analysis of a parallel ankle rehabilitation robot using modified sugeno inference system. / Jamwal, P. K.; Xie, S. Q.
39th International Symposium on Robotics, ISR 2008. 2008. p. 236-241.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Forward kinematic analysis of a parallel ankle rehabilitation robot using modified sugeno inference system
AU - Jamwal, P. K.
AU - Xie, S. Q.
PY - 2008
Y1 - 2008
N2 - Forward kinematics (FK) mapping for parallel mechanisms is difficult as it involves highly coupled nonlinear motions. Since FK is a key element in closed loop position and force control of parallel manipulators, an accurate prediction of end pose from the available link lengths is essential. This paper proposes a modified Sugeno Inference System (SIS) to accurately predict the forward mapping between joint and Cartesian coordinates. The SIS algorithm has been implemented on a new parallel robotic device, designed for flexible ankle rehabilitation treatments. To increase the accuracy of the SIS, antecedent fuzzy variables are tuned using a modified genetic algorithm and consequent crisp membership functions are trained with a gradient descent algorithm. It has been found that the proposed system provides better accuracy and is also time efficient, which makes it a better candidate for real time control applications.
AB - Forward kinematics (FK) mapping for parallel mechanisms is difficult as it involves highly coupled nonlinear motions. Since FK is a key element in closed loop position and force control of parallel manipulators, an accurate prediction of end pose from the available link lengths is essential. This paper proposes a modified Sugeno Inference System (SIS) to accurately predict the forward mapping between joint and Cartesian coordinates. The SIS algorithm has been implemented on a new parallel robotic device, designed for flexible ankle rehabilitation treatments. To increase the accuracy of the SIS, antecedent fuzzy variables are tuned using a modified genetic algorithm and consequent crisp membership functions are trained with a gradient descent algorithm. It has been found that the proposed system provides better accuracy and is also time efficient, which makes it a better candidate for real time control applications.
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M3 - Conference contribution
SP - 236
EP - 241
BT - 39th International Symposium on Robotics, ISR 2008
ER -