Evolutionary optimization of cubic polynomial joint trajectories for industrial robots

Kai Ming Tse; Chi-Hsu Wang

doi:10.1109/ICSMC.1998.726508

Evolutionary optimization of cubic polynomial joint trajectories for industrial robots

Kai Ming Tse^*, Chi-Hsu Wang

^*Corresponding author for this work

Department of Electrical and Computer Engineering

Research output: Contribution to journal › Conference article › peer-review

6 Scopus citations

Abstract

The conventional approach to find the constrained minimum-time path for a robot manipulator employs the trial-and-error procedure, namely the flexible polyhedron search method. In this paper we introduce an alternative approach by applying the genetic search algorithms to schedule the time intervals between each pair of adjacent knots such that the total traveling time is minimized subjected to the physical constraints on joint velocities, accelerations, and jerks. Modified heuristic crossover and a scaled and normed performance measure are applied to the genetic algorithmic searching procedures. Experiments with different combinations of crossover rates and mutation rates are carried out and the corresponding results outweigh the constrained minimum-time obtained from the trial-and-error polyhedron search method.

Original language	English
Pages (from-to)	3272-3276
Number of pages	5
Journal	Proceedings of the IEEE International Conference on Systems, Man and Cybernetics
Volume	4
DOIs	https://doi.org/10.1109/ICSMC.1998.726508
State	Published - 1 Dec 1998
Event	Proceedings of the 1998 IEEE International Conference on Systems, Man, and Cybernetics. Part 3 (of 5) - San Diego, CA, USA Duration: 11 Oct 1998 → 14 Oct 1998

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abstract = "The conventional approach to find the constrained minimum-time path for a robot manipulator employs the trial-and-error procedure, namely the flexible polyhedron search method. In this paper we introduce an alternative approach by applying the genetic search algorithms to schedule the time intervals between each pair of adjacent knots such that the total traveling time is minimized subjected to the physical constraints on joint velocities, accelerations, and jerks. Modified heuristic crossover and a scaled and normed performance measure are applied to the genetic algorithmic searching procedures. Experiments with different combinations of crossover rates and mutation rates are carried out and the corresponding results outweigh the constrained minimum-time obtained from the trial-and-error polyhedron search method.",

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AU - Tse, Kai Ming

AU - Wang, Chi-Hsu

PY - 1998/12/1

Y1 - 1998/12/1

N2 - The conventional approach to find the constrained minimum-time path for a robot manipulator employs the trial-and-error procedure, namely the flexible polyhedron search method. In this paper we introduce an alternative approach by applying the genetic search algorithms to schedule the time intervals between each pair of adjacent knots such that the total traveling time is minimized subjected to the physical constraints on joint velocities, accelerations, and jerks. Modified heuristic crossover and a scaled and normed performance measure are applied to the genetic algorithmic searching procedures. Experiments with different combinations of crossover rates and mutation rates are carried out and the corresponding results outweigh the constrained minimum-time obtained from the trial-and-error polyhedron search method.

AB - The conventional approach to find the constrained minimum-time path for a robot manipulator employs the trial-and-error procedure, namely the flexible polyhedron search method. In this paper we introduce an alternative approach by applying the genetic search algorithms to schedule the time intervals between each pair of adjacent knots such that the total traveling time is minimized subjected to the physical constraints on joint velocities, accelerations, and jerks. Modified heuristic crossover and a scaled and normed performance measure are applied to the genetic algorithmic searching procedures. Experiments with different combinations of crossover rates and mutation rates are carried out and the corresponding results outweigh the constrained minimum-time obtained from the trial-and-error polyhedron search method.

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DO - 10.1109/ICSMC.1998.726508

M3 - Conference article

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SP - 3272

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JO - Proceedings of the IEEE International Conference on Systems, Man and Cybernetics

JF - Proceedings of the IEEE International Conference on Systems, Man and Cybernetics

SN - 0884-3627

Y2 - 11 October 1998 through 14 October 1998

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Evolutionary optimization of cubic polynomial joint trajectories for industrial robots

Abstract

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