## ProceedingsIEEE Computer Society Press, 2003 - Artificial intelligence |

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Page 99

The gray - value at point ( x , y ) represents the

motion in direction of the corresponding vector í = ( a , ß , d ) without collision .

These two images represent all

The gray - value at point ( x , y ) represents the

**possible**maximal distance d ofmotion in direction of the corresponding vector í = ( a , ß , d ) without collision .

These two images represent all

**possible**mating directions and corresponding ...Page 125

The graph G construction starts with a dummy vertex vo . Each vertex of graph is

characterized by the corresponding set of operations ( state of part ) . For each

vertex v , we have a set of

create ...

The graph G construction starts with a dummy vertex vo . Each vertex of graph is

characterized by the corresponding set of operations ( state of part ) . For each

vertex v , we have a set of

**possible**blocks B ' ( v ) , which can be grouped tocreate ...

Page 151

Every

in this AND / OR graph . This is a

disassembly sequence . 1 Introduction Disassembly has become a promising ...

Every

**possible**disassembly sequence is represented with a connected subgraphin this AND / OR graph . This is a

**possible**starting point for selecting the optimumdisassembly sequence . 1 Introduction Disassembly has become a promising ...

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### Contents

P Lambert P Letier A Delchambre | 14 |

Scheduling | 16 |

Assembly Planning | 79 |

Copyright | |

6 other sections not shown

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### Common terms and phrases

actuator algorithm allows applied approach assembly planning assembly sequences assembly system assigned Automation blocks cell complete components computation configuration connected considered constraints corresponding cost cycle defined depends described determine developed device direction disassembly effect environment equation equipment evaluation example execution Figure final flexible force function geometric given graph grasping gripper holons IEEE International industrial initial integrated Introduction machining manipulation manufacturing measured mechanical method micro motion move nodes object obtained operation optimal orientation parameters path performance piezoelectric position possible precedence presented problem Proceedings programming proposed provides References relation representation represented respectively robot scheduling selected sensor shape shown shows simulation solution space step structure surface task Task Planning Technology tion tolerance torque transition virtual volume workstation