Title: Trajectory optimisation design of robot based on artificial intelligence algorithm

Authors: Li Huang; Kai Zhang; Wei Hu; Chengcheng Li

Addresses: College of Computer Science and Technology, Wuhan University of Science and Technology, Hubei, Wuhan 430081, China; Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System, Wuhan University of Science and Technology, Hubei, Wuhan 430081, China ' College of Computer Science and Technology, Wuhan University of Science and Technology, Hubei, Wuhan 430081, China; Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System, Wuhan University of Science and Technology, Hubei, Wuhan 430081, China ' College of Computer Science and Technology, Wuhan University of Science and Technology, Hubei, Wuhan 430081, China; Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System, Wuhan University of Science and Technology, Hubei, Wuhan 430081, China ' Key Laboratory of Metallurgical Equipment and Control Technology, Ministry of Education, Wuhan University of Science and Technology, Hubei, Wuhan 430081, China

Abstract: Artificial intelligence has attracted more and more attention and has been widely used in all walks of life, especially in the education industry; artificial intelligence has gradually become the core. Aiming at the problem of robot trajectory planning in artificial intelligence, this paper applies the project teaching method to the course of artificial intelligence, regards trajectory planning as a project, analyses and studies it, uses ant colony algorithm to find the optimal planning path. Through the teaching of the project, the students will understand the ant colony algorithm more deeply. The algorithm is programmed independently to achieve the final trajectory optimisation. Students become the main body of the classroom, give full play to the initiative and enthusiasm of the students, through the operation of the project to train the students' innovative ability and cooperation ability, and improve the overall quality of the college students.

Keywords: trajectory planning; project teaching method; artificial intelligence; ant colony algorithm.

DOI: 10.1504/IJWMC.2019.097420

International Journal of Wireless and Mobile Computing, 2019 Vol.16 No.1, pp.35 - 40

Received: 06 Aug 2018
Accepted: 26 Aug 2018
Published online: 21 Jan 2019 *

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