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Optimal trajectory generation in joint space for 6R industrial serial robots using cuckoo search algorithm

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Abstract

In this paper, an optimal trajectory generation approach is proposed based on optimal time, optimal jerk and optimal time-jerk by utilizing the interpolation spline methods. The methods including cubic spline, trigonometric spline and a combination of cubic spline and 7th-order polynomial are 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 three objectives, namely, minimizing total travelling time, minimizing mean jerk and minimizing a weighted sum of the travelling time and the mean jerk along the whole trajectory. The spline methods have been applied on PUMA-robot for optimizing the joint trajectories with the CS algorithm based on each objective. Moreover, results from the proposed algorithm have been compared with that of the algorithms suggested by earlier studies in terms of three objectives. With the trajectory planning methods, the joint velocities, accelerations and jerks along the whole trajectory optimized by CS meet the requirements of the kinematic constraints in case of each objective. Simulation results validated that the used trajectory planning methods based on the proposed algorithm are very effective in comparison with the same methods based on the algorithms proposed by earlier authors.

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Authors and Affiliations

  1. Department of Electronics and Communication Engineering, Kocaeli University, Kocaeli University, Kocaeli, Turkey

    Oğuzhan Karahan, Hasan Karci & Ali Tangel

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  1. Oğuzhan Karahan
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  2. Hasan Karci
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Correspondence to Hasan Karci.

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Karahan, O., Karci, H. & Tangel, A. Optimal trajectory generation in joint space for 6R industrial serial robots using cuckoo search algorithm. Intel Serv Robotics 15, 627–648 (2022). https://doi.org/10.1007/s11370-022-00440-8

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