A trajectory tracking application of redundant planar robot arm via support vector machines

Emre Sariyildiz*, Kemal Ucak, Gulay Oke, Hakan Temeltas

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

13 Citations (Scopus)

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 languageEnglish
Title of host publicationAdaptive and Intelligent Systems - Second International Conference, ICAIS 2011, Proceedings
Pages192-202
Number of pages11
DOIs
Publication statusPublished - 2011
Event2nd International Conference on Adaptive and Intelligent Systems, ICAIS 2011 - Klagenfurt, Austria
Duration: 6 Sept 20118 Sept 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6943 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference2nd International Conference on Adaptive and Intelligent Systems, ICAIS 2011
Country/TerritoryAustria
CityKlagenfurt
Period6/09/118/09/11

Keywords

  • Artificial Neural Networks
  • Redundancy
  • Robot Arm
  • Singularity
  • Support Vector Machine
  • Trajectory Tracking

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