Energy and Path Optimization of Robot Arm Simulator Via Multi-Objective Evolutionary Algorithm

  • Authors

    • Z. Mohamed
    • N. S. Khusaini
    • M. A.M Anuar
    • R. Ramly
    • M. A Anuar
    • K. S.M Sahari
    2018-12-09
    https://doi.org/10.14419/ijet.v7i4.36.28150
  • Robot arm, Genetic algorithm, Neural network, Multi-objective evolutionary algorithm.

  • Abstract

    The performance of robot arm motion generated via neural network are presented in this paper. The robot arm motion for obstacle avoidance simultaneously optimizing three functions; minimum distance, minimum time and minimum energy are generated. Four different initial and goal position had been chosen to test and analyze the performance of generated neural controller. The same neural controllers can be employed to a different range of initial and goal position. The motion generated yield good results in the simulator. In this research a new approach for intelligent robot arm path and motion generation are successfully implemented.

     

  • References

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  • How to Cite

    Mohamed, Z., S. Khusaini, N., A.M Anuar, M., Ramly, R., A Anuar, M., & S.M Sahari, K. (2018). Energy and Path Optimization of Robot Arm Simulator Via Multi-Objective Evolutionary Algorithm. International Journal of Engineering & Technology, 7(4.36), 404-408. https://doi.org/10.14419/ijet.v7i4.36.28150

    Received date: 2019-03-03

    Accepted date: 2019-03-03

    Published date: 2018-12-09