Time-optimal trajectory generation in joint space for 6R industrial serial robots using Cuckoo search algorithm

Main Article Content

Oguzhan Karahan
Hasan Karci
Ali Tangel

Abstract

The trajectory planning problem in industrial robotic applications has recently attracted the great attention of many researchers. In this paper, an optimal trajectory planning approach is proposed based on optimal time by utilizing the interpolation spline method. The method including a combination of cubic spline and 7th order polynomial is used for generating the trajectory in joint space for robot manipulators. Cuckoo Search (CS) optimization algorithm is chosen to optimize the joint trajectories based on objective, including minimizing total traveling time along the whole trajectory. The spline method has been applied to the PUMA robot for optimizing the joint trajectories with the CS algorithm based on the objective. With the trajectory planning method, the joint velocities, accelerations, and jerks along the whole trajectory optimized by CS meet the requirements of the kinematic constraints in the case of the objective. Simulation results validated that the used trajectory planning method based on the proposed algorithm is very effective in comparison with the same methods based on the algorithms proposed by earlier authors.


 


Keywords: CS; industrial robots; interpolation; spline methods; trajectory planning.

Downloads

Download data is not yet available.

Article Details

How to Cite
Karahan, O., Karci, H., & Tangel, A. (2022). Time-optimal trajectory generation in joint space for 6R industrial serial robots using Cuckoo search algorithm. Global Journal of Computer Sciences: Theory and Research, 12(1), 42–54. https://doi.org/10.18844/gjcs.v12i1.7447
Section
Articles