Automatic variation-point identification in function-block-based models

2011 ◽  
Vol 46 (2) ◽  
pp. 23-32 ◽  
Author(s):  
Uwe Ryssel ◽  
Joern Ploennigs ◽  
Klaus Kabitzsch
2020 ◽  
Vol 66 ◽  
pp. 101994 ◽  
Author(s):  
Wei Fan ◽  
Lianyu Zheng ◽  
Wei Ji ◽  
Xun Xu ◽  
Lihui Wang ◽  
...  

Author(s):  
Sichao Liu ◽  
Lihui Wang ◽  
Xi Vincent Wang

AbstractIn 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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