A Skill Programming Method Based on Assembly Motion Primitive for Modular Assembly System
نویسندگان
چکیده
To improve the programming efficiency of automatic assembly system, a novel skill framework based on task learning is proposed for modular system in this paper. In framework, motion sequence skills can be modeled by demonstration data. And represented hierarchically. A complete process part divided into several skills, and each sequential primitives (AMP) multiple modules. Then, method Hidden Markov Model proposed, maximum probability used to generate optimal AMP. Each AMP input form instruction assembly. Aiming at problem accurate positioning trajectory planning, visual guidance direct teaching are settle problem. evaluate viability customized acquire data, graphical user interface (GUI) software designed. Five learned. Experimental conducted validate effectiveness method.
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ژورنال
عنوان ژورنال: IEEE Access
سال: 2021
ISSN: ['2169-3536']
DOI: https://doi.org/10.1109/access.2021.3080838