Using an Improved Artificial Hummingbird Algorithm for Vision-Guided Optimization And Grasping of Multi-Objective Robots

Rui Yang; Qian Zhou; Qinglong Mo; Lin Gan; Ruihan Hu

doi:10.1088/1742-6596/2365/1/012052

Using an Improved Artificial Hummingbird Algorithm for Vision-Guided Optimization And Grasping of Multi-Objective Robots

Rui Yang
, Qian Zhou^*
, Qinglong Mo
, Lin Gan
, Ruihan Hu^*

^*Corresponding author for this work

Institute of Intelligent Manufacturing, Guangdong Academy of Sciences
Chaozhou Zhongchao Intelligent Manufacturing Innovation Center
National University of Defense Technology
State Key Laboratory of Pulsed Power Laser Technology
Key Laboratory of Electronic Restriction of Anhui Province

Research output: Contribution to journal › Conference article › peer-review

2 Scopus citations

Abstract

AHA (artificial hummingbird algorithm) is a meta-heuristic optimization algorithm that simulates the unique flight and feeding patterns of hummingbirds. By combining the excellent strategy of the artificial hummingbird algorithm with the framework of the multi-objective optimization algorithm, the multi-objective artificial hummingbird algorithm is created, improved, and further enhanced. Therefore, the research on vision-guided optimization and grasping control of multi-objective robots based on an enhanced artificial hummingbird algorithm has significant academic significance and vast potential for application.

Original language	English
Article number	012052
Journal	Journal of Physics: Conference Series
Volume	2365
Issue number	1
DOIs	https://doi.org/10.1088/1742-6596/2365/1/012052
State	Published - 2022
Externally published	Yes
Event	2022 3rd International Conference on Internet of Things, Artificial Intelligence and Mechanical Automation, IoTAIMA 2022 - Shanghai, China Duration: 22 Jul 2022 → 24 Jul 2022

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title = "Using an Improved Artificial Hummingbird Algorithm for Vision-Guided Optimization And Grasping of Multi-Objective Robots",

abstract = "AHA (artificial hummingbird algorithm) is a meta-heuristic optimization algorithm that simulates the unique flight and feeding patterns of hummingbirds. By combining the excellent strategy of the artificial hummingbird algorithm with the framework of the multi-objective optimization algorithm, the multi-objective artificial hummingbird algorithm is created, improved, and further enhanced. Therefore, the research on vision-guided optimization and grasping control of multi-objective robots based on an enhanced artificial hummingbird algorithm has significant academic significance and vast potential for application.",

author = "Rui Yang and Qian Zhou and Qinglong Mo and Lin Gan and Ruihan Hu",

note = "Publisher Copyright: {\textcopyright} 2022 Institute of Physics Publishing. All rights reserved.; 2022 3rd International Conference on Internet of Things, Artificial Intelligence and Mechanical Automation, IoTAIMA 2022 ; Conference date: 22-07-2022 Through 24-07-2022",

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T1 - Using an Improved Artificial Hummingbird Algorithm for Vision-Guided Optimization And Grasping of Multi-Objective Robots

AU - Yang, Rui

AU - Zhou, Qian

AU - Mo, Qinglong

AU - Gan, Lin

AU - Hu, Ruihan

PY - 2022

Y1 - 2022

N2 - AHA (artificial hummingbird algorithm) is a meta-heuristic optimization algorithm that simulates the unique flight and feeding patterns of hummingbirds. By combining the excellent strategy of the artificial hummingbird algorithm with the framework of the multi-objective optimization algorithm, the multi-objective artificial hummingbird algorithm is created, improved, and further enhanced. Therefore, the research on vision-guided optimization and grasping control of multi-objective robots based on an enhanced artificial hummingbird algorithm has significant academic significance and vast potential for application.

AB - AHA (artificial hummingbird algorithm) is a meta-heuristic optimization algorithm that simulates the unique flight and feeding patterns of hummingbirds. By combining the excellent strategy of the artificial hummingbird algorithm with the framework of the multi-objective optimization algorithm, the multi-objective artificial hummingbird algorithm is created, improved, and further enhanced. Therefore, the research on vision-guided optimization and grasping control of multi-objective robots based on an enhanced artificial hummingbird algorithm has significant academic significance and vast potential for application.

UR - https://www.scopus.com/pages/publications/85142506943

U2 - 10.1088/1742-6596/2365/1/012052

DO - 10.1088/1742-6596/2365/1/012052

M3 - 会议文章

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VL - 2365

JO - Journal of Physics: Conference Series

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IS - 1

M1 - 012052

T2 - 2022 3rd International Conference on Internet of Things, Artificial Intelligence and Mechanical Automation, IoTAIMA 2022

Y2 - 22 July 2022 through 24 July 2022

ER -

Using an Improved Artificial Hummingbird Algorithm for Vision-Guided Optimization And Grasping of Multi-Objective Robots

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