ProceedingsIEEE Computer Society Press, 2001 - Artificial intelligence |
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Page 1
To solve the optimization problem , we used an objective function consisting of a
goal term , a smoothness term and a ... we propose a theoretical method using
reinforcement learning for adjusting weight parameters in the objective functions .
To solve the optimization problem , we used an objective function consisting of a
goal term , a smoothness term and a ... we propose a theoretical method using
reinforcement learning for adjusting weight parameters in the objective functions .
Page 6
In a multi - robot system , interactions between robots can be expressed as terms
in the objective function Ev . If a user wants to move two robots keeping them
close to or avoiding each other , it is sufficient to introduce an attractive or
repulsion ...
In a multi - robot system , interactions between robots can be expressed as terms
in the objective function Ev . If a user wants to move two robots keeping them
close to or avoiding each other , it is sufficient to introduce an attractive or
repulsion ...
Page 389
When any machine performs ing and function or property verification . The
proposed human desired functions , it operates with changes in its lo approach
applies state - based models to model the machine cation , shape , attributes , or
the ...
When any machine performs ing and function or property verification . The
proposed human desired functions , it operates with changes in its lo approach
applies state - based models to model the machine cation , shape , attributes , or
the ...
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Contents
Session MIB Assembly Planning Room | 31 |
Session MIC Production System1 Room C | 61 |
Session M2A Planning Control of Manipulators Room | 92 |
Copyright | |
11 other sections not shown
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Common terms and phrases
algorithm analysis applied approach assembly automatic Automation calculated called cell combination complex components computed condition connected considered constraints coordinate corresponding cost defined described determined developed direction disassembly dynamic edge effect Engineering environment equipment error evaluation example execution experiments Figure finger flexible force function geometric given graph grasp holons IEEE initial integrated International introduced Japan joint machine manipulation manufacturing material means measured mechanical method mobile robot module motion movement moving node object obstacles obtained operation optimal orientation parameters path performed planning position possible presented problem Proceedings proposed reference region relation represented Research respectively robot rotation rules scheduling selection sensor sequence shown shows simulation solutions space specific station step structure subassembly surface Table task tion tolerance tool trajectory transition