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Time Optimal Robot Trajectory Planning Using Intelligent Algorithms


Affiliations
1 Dept. of Mechanical Engg., Kumaraguru College of Technology, Coimbatore, India
2 J.J. College of Engg. and Technology, Trichy, India
     

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The minimum-time path for a robot arm has been a long standing and unsolved problem of considerable interest. This paper presents two intelligent optimization algorithms such as genetic algorithm (GA) and particle swarm optimization (PSO) for obtaining minimum time paths for robot manipulators. To illustrate the proposed methods, time optimal trajectories for a two-link IBM planar robot Is considered in this work. The results obtained using the proposed GA and PSO are compared with neural network results equations. It Is proved from this paper that the proposed intelligent optimization algorithms can be used successfully to find optimal travel time by approximating the robot inverse dynamics. Also both proposed GA and PSO methods give better results than the neural network.
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  • Time Optimal Robot Trajectory Planning Using Intelligent Algorithms

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Authors

R. Saravanan
Dept. of Mechanical Engg., Kumaraguru College of Technology, Coimbatore, India
S. Ramabalan
J.J. College of Engg. and Technology, Trichy, India
M. Thilak
J.J. College of Engg. and Technology, Trichy, India

Abstract


The minimum-time path for a robot arm has been a long standing and unsolved problem of considerable interest. This paper presents two intelligent optimization algorithms such as genetic algorithm (GA) and particle swarm optimization (PSO) for obtaining minimum time paths for robot manipulators. To illustrate the proposed methods, time optimal trajectories for a two-link IBM planar robot Is considered in this work. The results obtained using the proposed GA and PSO are compared with neural network results equations. It Is proved from this paper that the proposed intelligent optimization algorithms can be used successfully to find optimal travel time by approximating the robot inverse dynamics. Also both proposed GA and PSO methods give better results than the neural network.