Recently, by increasing the productivity of industrial manufacture, industrial robots have played a key role in many fields of industry (e.g. automobile production, food production, etc.) However, there are two problems rarely mentioned in this field. First, compared with automatization in other fields, industrial robots are programmed manually by a human operator. Second, because of the physical difference between robots and difference of operating platform, there doesnât exist a general method to define the skill (motion records) of robots and make it possible to reuse the skills between robots. In this work, we are trying to propose a skill definition of transfer system which combine the strengths of traditional DMP algorithm and deep learning method. Specifically, in our method, a set of motion primitive bases are generated from motion records in different robots. Skills are re-defined by the linear coefficient of the primitive bases and transferred based on motion primitive bases translation between different platforms. Experiment shows that our method can successfully transfer skills between different models with less space requirement.
| Identifer | oai:union.ndltd.org:VANDERBILT/oai:VANDERBILTETD:etd-04062017-164218 |
| Date | 07 April 2017 |
| Creators | Lan, Ke |
| Contributors | D. Mitchell Wilkes, Richard Alan Peters |
| Publisher | VANDERBILT |
| Source Sets | Vanderbilt University Theses |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | http://etd.library.vanderbilt.edu/available/etd-04062017-164218/ |
| Rights | unrestricted, I hereby certify that, if appropriate, I have obtained and attached hereto a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dissertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to Vanderbilt University or its agents the non-exclusive license to archive and make accessible, under the conditions specified below, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report. |
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