NDLI: Optimal time-jerk trajectory planning for industrial robots

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Optimal time-jerk trajectory planning for industrial robots

Content Provider	Semantic Scholar
Author	Huang, J. Hu, Pengfei Wu, Kaiyuan Zeng, Min
Copyright Year	2018
Abstract	A methodology for time-jerk synthetic optimal trajectory planning of robotic manipulators is described in this paper. The trajectory is interpolated in the joint space by means of 5thorder B-spline and then optimized by the elitist non-dominated sorting genetic algorithm (NSGA-II) for two objectives, namely, traveling time and mean jerk along the whole trajectory. 5th-order B-spline interpolation technique enables the trajectory to be constrained in the kinematic limits of velocity, acceleration, and jerk while satisfying the continuity of jerk. NSGA-II as a multi-objective optimization technique is used to address the time-jerk optimal trajectory planning problem. The obtained Pareto optimal front provides decisionmakers flexible selections on non-dominated solutions for industrial applications. Two performance measures are presented to evaluate the strength of the Pareto optimal front and to select the best optimal solution respectively. Simulations and experiments validate the effectiveness and practicability of the proposed methodology in comparison with those provided by another important trajectory planning methodology. © 2017 Elsevier Ltd. All rights reserved.
File Format	PDF HTM / HTML
Alternate Webpage(s)	http://isiarticles.com/bundles/Article/pre/pdf/104447.pdf
Language	English
Access Restriction	Open
Subject Keyword	B-spline Computer simulation Experiment Genetic algorithm Industrial robot Interpolation Imputation Technique Mathematical optimization Multi-objective optimization Numerous Pareto efficiency Planning Techniques Robot (device) Scott continuity Solutions Sorting Spline interpolation Synthetic intelligence Temporomandibular Joint Disorders Velocity (software development) travel
Content Type	Text
Resource Type	Article

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