Title
Using robust and simplified geometric models in skill-based manipulation
Abstract
Manipulator tasks such as assembly and disassembly can generally be divided into several motion primitives. We call these "skills" and explain how most manipulator tasks can be composed of skill sequences. Skills are also used to compensate for errors both in the geometric model and in manipulator motions. There are dispensable data in the shapes, positions and orientations of objects when achieving skill motions in a task Therefore, we can derive simplified geometric models by considering both dispensable and indispensable data in a skill motion. We call such robust and simplified models "false models." This paper describes our definition of false models in planning and visual sensing and shows the effectiveness of our method using examples
Year
DOI
Venue
2001
10.1109/IROS.2001.973349
Intelligent Robots and Systems, 2001. Proceedings. 2001 IEEE/RSJ International Conference
Keywords
Field
DocType
assembling,error compensation,manipulators,assembly,disassembly,error compensation,manipulator tasks,robust simplified geometric models,skill sequences,skill-based manipulation
Motion planning,Computer vision,Machine vision,Computer science,Geometric modeling,Manipulator,Robustness (computer science),Control engineering,Solid modeling,Artificial intelligence,Motion analysis
Conference
Volume
ISBN
Citations 
1
0-7803-6612-3
3
PageRank 
References 
Authors
0.51
5
4
Name
Order
Citations
PageRank
Akira Nakamura1255.05
T. Ogasawara26811.15
Kitagaki, K.3553.61
Takashi Suehiro430.51