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Neural Network approach to Visual Servoing for Robotic Hand Eye Coordination
| Content Provider | Semantic Scholar |
|---|---|
| Author | Shree, Atulya Shivam Babu, N. Srujan Kumar, Ravi Ranjan |
| Copyright Year | 2013 |
| Abstract | This paper deals with a neural network approach to visual servoing for control of robotic manipulator. Our method is entirely on visual feedback and doesn’t require any prior information about geometry or pose of robotic manipulator or calibration of cameras. With the data of end effector’s position and orientation and goal(in image coordinates) error signal is used to move the manipulator. Two different approaches were discussed in this paper to solve inverse kinematics problem using neural networks approach. Self learning neural controller learns the inverse kinematics of robotic manipulator. Approach is illustrated with experiments of visual feedback controlled robotic manipulator and simulations of results. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://home.iitk.ac.in/~atulya/docs/Term_Project_ME762.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
