Fuzzy membership function based neural networks with applications to the visual servoing of robot manipulators

@article{Suh1994FuzzyMF,
  title={Fuzzy membership function based neural networks with applications to the visual servoing of robot manipulators},
  author={Il Hong Suh and Tae Won Kim},
  journal={IEEE Trans. Fuzzy Syst.},
  year={1994},
  volume={2},
  pages={203-220}
}
It is shown that there exists a nonlinear mapping which transforms image features and their changes to the desired camera motion without measuring of the relative distance between the camera and the object. This nonlinear mapping can eliminate several difficulties occurring in computing the inverse of the feature Jacobian as in the usual feature-based visual feedback control methods. Instead of analytically deriving the closed form of this mapping, a fuzzy membership function (FMF) based neural… 
View via Publisher
incorl.hanyang.ac.kr
66 Citations
Highly Influential Citations
2
Background Citations
17
Methods Citations
20
Results Citations
1

66 Citations

Citation Type

Citation Type

A visual servoing algorithm using fuzzy logics and fuzzy-neural networks
  • I. Suh, Tae Won Kim
  • Computer Science
    Proceedings of IEEE International Conference on Robotics and Automation
  • 1996
A visual servoing algorithm is proposed for a robot with a camera in hand, where fuzzy logics and fuzzy-neural networks are employed to represent and/or learn camera motion commands to track a moving…
A Visual St:rvoing Algorithm using Fuzzy Logicis and Fuzzy-Neural Networks
A visual servoing algorithm is proposed for a robot with a camera in hand, where fuzzy logics and fuzzy-neural networks are employed to represent and/or learn camera motion commands to track a moving…
Fuzzy Model Based Control Applied to Image-Based Visual Servoing
TLDR
A new approach to eye-in-hand image-based visual servoing based on fuzzy modeling and control based on inverse fuzzy model and fuzzy compensator, which can follow a point-to-point pre-defined trajectory faster (or smoother) than the classic approach.
A fuzzy-neural-network-based visual feedback learning control for robot manipulators
  • I. Suh, Tae Won Kim
  • Computer Science
    Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94)
  • 1994
A visual feedback learning control algorithm is proposed for a robot manipulator equipped with joint position servos employing fuzzy-membership-function-based neural networks (FMFNN), where…
Adaptive neural network-based visual servoing control for manipulator with unknown output nonlinearities
Vision Based Robot Manipulator Control with Neural Modeling of Jacobian Matrix
Visual servoing system is a system to control a robot by visual feedback so that robot drives from any arbitrary start position to target positions. Various ways, including control by using model of…
Image Recognition Applied to Robot Control Using Fuzzy Modeling
TLDR
The obtained experimental results show the effectiveness of the proposed control scheme: the fuzzy controller can follow a point-to-point pre-defined trajectory faster (or smoother) than the classic approach.
On Evolving Fuzzy Modeling for Visual Control of Robotic Manipulators
TLDR
Experimental results obtained in a PUMA robot performing eye-to-hand visual servoing in 3D workspace are used to demonstrate the validity of the proposed approach, when compared to the previous developed off-line learning.
Learning Approaches to Visual Control of Robotic Manipulators
TLDR
The off-line fuzzy model was used to control the robot, which clearly shows the effectiveness of the approach, and the approaches used are fuzzy modeling, neural networks and support vector machines.
Uncalibrated Eye-to-Hand Visual Servoing Using Inverse Fuzzy Models
TLDR
A new uncalibrated eye-to-hand visual servoing based on inverse fuzzy modeling that is independent from the robot's kinematic model or camera calibration and also avoids the necessity of inverting the Jacobian online is proposed.
...
...

References

SHOWING 1-10 OF 35 REFERENCES
Real-time application of neural networks for sensor-based control of robots with vision
  • W. Miller
  • Computer Science
    IEEE Trans. Syst. Man Cybern.
  • 1989
A practical neural network-based learning control system is described that is applicable to complex robotic systems involving multiple feedback sensors and multiple command variables. In the…
Visual servo control of robotic manipulators based on artificial neural network
TLDR
A control scheme for a robotic manipulator system which uses visual information to position and orient the end effector without any geometric process of the position and orientation and without inverse kinematic calculation is described.
Self-Organizing Visual Servo System based on Neural Networks
TLDR
A neural network based self-organing control concept for a robotic manipulator that organizes itself for any manipulator configuration by learning the nonlinear mapping between image data and joint angles using two neural networks.
Visual servoing by a fuzzy reasoning method
TLDR
A visual servoing method is proposed for eye-in-hand robots that employs a self-organizing fuzzy controller that obtains an analytic form of the proposed Jacobian to alleviate difficulties in real-time implementation.
Sensor-based control of robotic manipulators using a general learning algorithm
  • W. Miller
  • Computer Science
    IEEE J. Robotics Autom.
  • 1987
TLDR
The results of two learning experiments using a General Electric P-5 manipulator are presented and control system performance was found to be limited by the resolution of the sensor feedback data, rather than by control structure limitations.
Weighted selection of image features for resolved rate visual feedback control
The authors develop methodologies for the automatic selection of image features to be used to visually control the relative position and orientation (pose) between the end-effector of an eye-in-hand…
Fuzzy basis functions, universal approximation, and orthogonal least-squares learning
TLDR
Using the Stone-Weierstrass theorem, it is proved that linear combinations of the fuzzy basis functions are capable of uniformly approximating any real continuous function on a compact set to arbitrary accuracy.
Regularization Algorithms for Learning That Are Equivalent to Multilayer Networks
TLDR
A theory is reported that shows the equivalence between regularization and a class of three-layer networks called regularization networks or hyper basis functions.
Image-Based Visual Servo Control Of Robots
TLDR
Analysis and simulation of model reference adaptive control structures have shown that with proper attention to regimes of operation and priority among features, image-based control of multi-degree-of-freedom systems may provide improved dynamic performance due to reduction in image interpretation computational load and estimation noise.
Resolved-acceleration control of mechanical manipulators
Position control of a manipulator involves the practical problem of solving for the correct input torques to apply to the joints for a set of specified positions, velocities, and accelerations. Since…
...
...