A Bio-inspired trajectory planning method for robotic manipulators based on improved bacteria foraging optimization algorithm and tau theory

Zhiqiang Wang; Jinzhu Peng; Shuai Ding; Zhiqiang Wang; Jinzhu Peng; Shuai Ding

doi:10.3934/mbe.2022029

Mathematical Biosciences and Engineering

2022, Volume 19, Issue 1: 643-662. doi: 10.3934/mbe.2022029

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Research article

A Bio-inspired trajectory planning method for robotic manipulators based on improved bacteria foraging optimization algorithm and tau theory

School of Electrical Engineering, Zhengzhou University, No. 100 of Science Avenue, Zhengzhou 450001, China

Academic Editor: Yang Kuang

Received: 28 August 2021 Accepted: 01 November 2021 Published: 18 November 2021

In this paper, a novel bio-inspired trajectory planning method is proposed for robotic systems based on an improved bacteria foraging optimization algorithm (IBFOA) and an improved intrinsic Tau jerk (named Tau-J*) guidance strategy. Besides, the adaptive factor and elite-preservation strategy are employed to facilitate the IBFOA, and an improved Tau-J* with higher-order of intrinsic guidance movement is used to avoid the nonzero initial and final jerk, so as to overcome the computational burden and unsmooth trajectory problems existing in the optimization algorithm and traditional interpolation algorithm. The IBFOA is utilized to determine a small set of optimal control points, and Tau-J* is then invoked to generate smooth trajectories between the control points. Finally, the results of simulation tests demonstrate the eminent stability, optimality, and rapidity capability of the proposed bio-inspired trajectory planning method.
- robotic manipulator,
- trajectory planning,
- improved bacteria foraging optimization algorithm,
- Tau theory,
- interpolation algorithm,
- multi-objective optimization
Citation: Zhiqiang Wang, Jinzhu Peng, Shuai Ding. A Bio-inspired trajectory planning method for robotic manipulators based on improved bacteria foraging optimization algorithm and tau theory[J]. Mathematical Biosciences and Engineering, 2022, 19(1): 643-662. doi: 10.3934/mbe.2022029

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Abstract

In this paper, a novel bio-inspired trajectory planning method is proposed for robotic systems based on an improved bacteria foraging optimization algorithm (IBFOA) and an improved intrinsic Tau jerk (named Tau-J*) guidance strategy. Besides, the adaptive factor and elite-preservation strategy are employed to facilitate the IBFOA, and an improved Tau-J* with higher-order of intrinsic guidance movement is used to avoid the nonzero initial and final jerk, so as to overcome the computational burden and unsmooth trajectory problems existing in the optimization algorithm and traditional interpolation algorithm. The IBFOA is utilized to determine a small set of optimal control points, and Tau-J* is then invoked to generate smooth trajectories between the control points. Finally, the results of simulation tests demonstrate the eminent stability, optimality, and rapidity capability of the proposed bio-inspired trajectory planning method.

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