Abstract
In order to improve the effect of intelligent robot motion planning, this paper combines machine vision to conduct intelligent robot motion trajectory planning and analysis, and analyze the motion trajectory in complex environments. Aiming at the problem that the dynamic motion primitive algorithm is only suitable for an ideal and fixed motion environment during the demonstration and learning process, this paper proposes a robot motion trajectory control based on the ant colony algorithm, and proposes an ant colony optimization algorithm with self-adjusting the number of ants. The factors that affect the number of ants is the distance between the start point and the end point and the complexity of the map environment. After constructing an intelligent robot based on machine vision, based on the motion trajectory planning model, this paper collects data through machine vision, and realizes the intelligent planning and control of robot motion based on the motion planning algorithm. Through experimental research, it can be known that the intelligent robot system based on machine vision constructed in this paper can identify obstacles in complex environments and carry out reasonable trajectory planning.
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Funding
This work was supported by: The Province Natural Science Foundation of Hunan (No. 2019JJ50477); The grants from the Huaihua University Project (No.HHUY2019-25); Huaihua Social Science Achievements Evaluation Committee Project (No.XSP20YBC199); The Huaihua University Double First-Class initiative Applied Characteristic Discipline of Control Science and Engineering.
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Liu, Y., Zhang, X., Qu, T. et al. Intelligent robot motion trajectory planning based on machine vision. Int J Syst Assur Eng Manag 14, 776–785 (2023). https://doi.org/10.1007/s13198-021-01559-0
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DOI: https://doi.org/10.1007/s13198-021-01559-0