Function Block-Based Multimodal Control for Symbiotic Human–Robot Collaborative AssemblySource: Journal of Manufacturing Science and Engineering:;2021:;volume( 143 ):;issue: 009::page 091001-1DOI: 10.1115/1.4050187Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: In human–robot collaborative assembly, robots are often required to dynamically change their preplanned tasks to collaborate with human operators in close proximity. One essential requirement of such an environment is enhanced flexibility and adaptability, as well as reduced effort on the conventional (re)programming of robots, especially for complex assembly tasks. However, the robots used today are controlled by rigid native codes that cannot support efficient human–robot collaboration. To solve such challenges, this article presents a novel function block-enabled multimodal control approach for symbiotic human–robot collaborative assembly. Within the context, event-driven function blocks as reusable functional modules embedded with smart algorithms are used for the encapsulation of assembly feature-based tasks/processes and control commands that are transferred to the controller of robots for execution. Then, multimodal control commands in the form of sensorless haptics, gestures, and voices serve as the inputs of the function blocks to trigger task execution and human-centered robot control within a safe human–robot collaborative environment. Finally, the performed processes of the method are experimentally validated by a case study in an assembly work cell on assisting the operator during the collaborative assembly. This unique combination facilitates programming-free robot control and the implementation of the multimodal symbiotic human–robot collaborative assembly with the enhanced adaptability and flexibility.
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| contributor author | Liu, Sichao | |
| contributor author | Wang, Lihui | |
| contributor author | Wang, Xi Vincent | |
| date accessioned | 2022-02-05T21:44:08Z | |
| date available | 2022-02-05T21:44:08Z | |
| date copyright | 3/29/2021 12:00:00 AM | |
| date issued | 2021 | |
| identifier issn | 1087-1357 | |
| identifier other | manu_143_9_091001.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4276236 | |
| description abstract | In human–robot collaborative assembly, robots are often required to dynamically change their preplanned tasks to collaborate with human operators in close proximity. One essential requirement of such an environment is enhanced flexibility and adaptability, as well as reduced effort on the conventional (re)programming of robots, especially for complex assembly tasks. However, the robots used today are controlled by rigid native codes that cannot support efficient human–robot collaboration. To solve such challenges, this article presents a novel function block-enabled multimodal control approach for symbiotic human–robot collaborative assembly. Within the context, event-driven function blocks as reusable functional modules embedded with smart algorithms are used for the encapsulation of assembly feature-based tasks/processes and control commands that are transferred to the controller of robots for execution. Then, multimodal control commands in the form of sensorless haptics, gestures, and voices serve as the inputs of the function blocks to trigger task execution and human-centered robot control within a safe human–robot collaborative environment. Finally, the performed processes of the method are experimentally validated by a case study in an assembly work cell on assisting the operator during the collaborative assembly. This unique combination facilitates programming-free robot control and the implementation of the multimodal symbiotic human–robot collaborative assembly with the enhanced adaptability and flexibility. | |
| publisher | The American Society of Mechanical Engineers (ASME) | |
| title | Function Block-Based Multimodal Control for Symbiotic Human–Robot Collaborative Assembly | |
| type | Journal Paper | |
| journal volume | 143 | |
| journal issue | 9 | |
| journal title | Journal of Manufacturing Science and Engineering | |
| identifier doi | 10.1115/1.4050187 | |
| journal fristpage | 091001-1 | |
| journal lastpage | 091001-10 | |
| page | 10 | |
| tree | Journal of Manufacturing Science and Engineering:;2021:;volume( 143 ):;issue: 009 | |
| contenttype | Fulltext |