الگوریتم بهینه سازی ازدحام معلق ها
ترجمه نشده

الگوریتم بهینه سازی ازدحام معلق ها

عنوان فارسی مقاله: الگوریتم بهینه سازی ازدحام معلق های برنامه ریزی مسیر جدید برای برنامه ریزی مسیر بازوهای مکانیکی روبات
عنوان انگلیسی مقاله: A New Trajectory-Planning Beetle Swarm Optimization Algorithm for Trajectory Planning of Robot Manipulators
مجله/کنفرانس: دسترسی – IEEE Access
رشته های تحصیلی مرتبط: مهندسی کامپیوتر، مهندسی برق
گرایش های تحصیلی مرتبط: مهندسی الگوریتم و محاسبات، رباتیک
کلمات کلیدی فارسی: بهینه سازی ازدحام معلق ها، بازوهای مکانیکی روبات، برنامه ریزی مسیر، الگوریتم های بهینه سازی، سیستم های کنترل
کلمات کلیدی انگلیسی: Beetle swarm optimization, robot manipulators, trajectory planning, optimization algorithms, control systems
نوع نگارش مقاله: مقاله پژوهشی (Research Article)
شناسه دیجیتال (DOI): https://doi.org/10.1109/ACCESS.2019.2949271
دانشگاه: Department of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou 310018, China
صفحات مقاله انگلیسی: 15
ناشر: آی تریپل ای - IEEE
نوع ارائه مقاله: ژورنال
نوع مقاله: ISI
سال انتشار مقاله: 2019
ایمپکت فاکتور: 4.641 در سال 2018
شاخص H_index: 56 در سال 2019
شاخص SJR: 0.609 در سال 2018
شناسه ISSN: 2169-3536
شاخص Quartile (چارک): Q2 در سال 2018
فرمت مقاله انگلیسی: PDF
وضعیت ترجمه: ترجمه نشده است
قیمت مقاله انگلیسی: رایگان
آیا این مقاله بیس است: خیر
آیا این مقاله مدل مفهومی دارد: ندارد
آیا این مقاله پرسشنامه دارد: ندارد
آیا این مقاله متغیر دارد: ندارد
کد محصول: E13906
رفرنس: دارای رفرنس در داخل متن و انتهای مقاله
فهرست مطالب (انگلیسی)

Abstract

I. Introduction

II. Preliminaries

III. Methodology

IV. Simulation Studies and Comparisons

V. Conclusion and Future Work

Authors

Figures

References

بخشی از مقاله (انگلیسی)

Abstract

Based on a heuristic optimization algorithm, this paper proposes a new algorithm named trajectory-planning beetle swarm optimization (TPBSO) algorithm for solving trajectory planning of robots, especially robot manipulators. Firstly, two specific manipulator trajectory planning problems are presented as the practical application of the algorithm, which are point-to-point planning and fixed-geometric-path planning. Then, in order to verify the effectiveness of the algorithm, this paper develops a control model and conducts numerical experiments on two planning tasks. Moreover, it compares with existing algorithms to show the superiority of our proposed algorithm. Finally, the results of numerical comparisons show that algorithm has a relatively faster computational speed and better control performance without increasing computational complexity.

Introduction

The robotic arm, or the manipulator, has similar functions to a human arm and can be either a separate mechanism or part of a more complex robot [1]. It can be considered that the link of the robot arm forms a kinematic chain, and the end of the kinematic chain is called an end-effector for performing actual operations such as grasping, spraying, cutting, etc. The robotic arm is widely used in modern society. In the field of industrial manufacturing, it is used for assembly, spraying, welding etc [2]. In the medical field, it is used as a surgical aid [3], [4]. And in agriculture, for picking vegetables and fruits. Even in space exploration the robotic arm can also find its application. In the research area of robot manipulator, trajectory planning has always been a hot spot, which is usually performed with constraints that may come from dynamic equations or from the inputs [5]. There are several important issues in the study of manipulator trajectory planning, one of which is the solution of inverse kinematics transformation [6]–[10]. Due to the high nonlinearity of inverse kinematics transformation, the solution process is difficult. Therefore, improving the efficiency and effectiveness of inverse kinematics is very important in manipulator trajectory planning, especially in redundant manipulator trajectory planning [11]–[18]. The second is obstacle avoidance. In many manufacturing applications today, robot manipulators must use their endeffector to pass through the desired curve while their fuselage avoids collisions with obstacles in the environment.