Abstract
In this paper we present a kinematic based trajectory tracking application of redundant planar robot arm by using support vector machine method (SVM). The main advantages of using the proposed method are that, it does not suffer from singularity that is the main problem of redundancy in robot kinematics and better results for the kinematic model of redundant robot arm can be obtained by using less training data. Training data are obtained by using the forward differential kinematic model of the robot arm. We also implement the trajectory tracking application by using Artificial Neural Networks (ANN). Two methods are compared with respect to their generalization performances, and training performance. Simulation results are given.
Original language | English |
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Title of host publication | Adaptive and Intelligent Systems - Second International Conference, ICAIS 2011, Proceedings |
Pages | 192-202 |
Number of pages | 11 |
DOIs | |
Publication status | Published - 2011 |
Event | 2nd International Conference on Adaptive and Intelligent Systems, ICAIS 2011 - Klagenfurt, Austria Duration: 6 Sept 2011 → 8 Sept 2011 |
Publication series
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 6943 LNAI |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Conference
Conference | 2nd International Conference on Adaptive and Intelligent Systems, ICAIS 2011 |
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Country/Territory | Austria |
City | Klagenfurt |
Period | 6/09/11 → 8/09/11 |
Keywords
- Artificial Neural Networks
- Redundancy
- Robot Arm
- Singularity
- Support Vector Machine
- Trajectory Tracking