Robotics & Machine Learning Daily News2024,Issue(Feb.5) :82-83.DOI:10.3390/machines12010064

Researcher at Beijing Institute of Technology Targets Robotics (A Multi-Objective Trajectory Planning Method of the Dual-Arm Robot for Cabin Docking Based on the Modified Cuckoo Search Algorithm)

Robotics & Machine Learning Daily News2024,Issue(Feb.5) :82-83.DOI:10.3390/machines12010064

Researcher at Beijing Institute of Technology Targets Robotics (A Multi-Objective Trajectory Planning Method of the Dual-Arm Robot for Cabin Docking Based on the Modified Cuckoo Search Algorithm)

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Abstract

Current study results on robotics have been published. According to news reporting out of Beijing, People's Republic of China, by NewsRx editors, research stated, “During the assembly of mechanical systems, the dual-arm robot is always used for cabin docking.” Funders for this research include National Natural Science Foundation of China; Science And Technology Cooperation Project of Yunnan Province. Our news journalists obtained a quote from the research from Beijing Institute of Technology: “In order to ensure the accuracy and reliability of cabin docking, a multi-objective trajectory planning method for the dual-arm robot was proposed. A kinematic model of the dual-arm robot was constructed based on the Denavit-Hartenberg (D-H) method firstly. Then, in the Cartesian space, the end trajectory of the dual-arm robot was confirmed by the fifth-order B-spline curve. On the basis of a traditional multi-objective cuckoo search algorithm, a modified cuckoo algorithm was built using the improved initial population generation method and the step size. The total consumption time and joint impact were selected as the objective functions, the overall optimal solution for the modified cuckoo algorithm was obtained using the normalized evaluation method.”

Key words

Beijing Institute of Technology/Beijing/People’s Republic of China/Asia/Algorithms/Emerging Technologies/Machine Learning/Robot/Robotics/Search Algorithms

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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