Multi-objective optimization in industrial robot design and robotic cell design

Author: 
Xiaolong Feng, Daniel Wäppliong, and Hans Andersson (ABB, Chalmers University of Technology, Linköping University)

Task placement positions have significant impacts on robot performance: combined drive-train and task placement optimization explores better trade-offs between time performance and lifetime and between time performance and power consumption. Multi-objective optimization explores good insight for designers in robotic cell design. modeFRONTIER has contributed to our understanding of the robotic cell design optimization problems. We see increasing need in multi-objective optimizations in industrial robotic cell design , and robot family design.

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