Research on Environment Recognition and Task Planning Methods Using Image Information for Rescue Robots

2004 ◽  
Vol 2004.41 (0) ◽  
pp. 327-328
Author(s):  
Masatoshi Hatano ◽  
Haruki Obara ◽  
Hirofumi Takase ◽  
Shinichiro Saji
Author(s):  
Toshiharu Miwa ◽  
Kosuke Ishii

The acceleration of product development cycle continues to be a significant challenge for manufacturing firms around the world. This paper describes a task planning method for minimizing trial and error to reduce the development time in large-scale and complicated product development at the early stage of product development. The proposed method matches the group of product components according to geometry and determines the development sequence of each component to minimize the amount of feedback information across task groups. The method applies as evaluation index for task prioritization the product-sum of engineering interaction among components and worth of each component, the “worth flow.” The paper shows with an example of the generic hair drier with simple mechanical structure that this method contributes to the reduction of the size of task group by 22% and amount of information required for setting the interface links by 65% compared to the conventional planning methods.


1998 ◽  
Vol 36 (1-2) ◽  
pp. 101-111 ◽  
Author(s):  
Carlos Ramos ◽  
João Rocha ◽  
Zita Vale

1999 ◽  
Author(s):  
Greg R. Luecke ◽  
Kok-Leong Tan ◽  
Naci Zafer

2009 ◽  
Vol 28 (1) ◽  
pp. 104-126 ◽  
Author(s):  
Stéphane Cambon ◽  
Rachid Alami ◽  
Fabien Gravot

Author(s):  
Zhiming Ji

Abstract Development in parallel-actuated platform manipulators has opened new applications. Proper placement of a platform manipulator is important for it to meet different workspace and other task requirement. We formulate the placement of platform manipulators with triangle-shaped mobile plate as an optimization problem. This paper presents the derivation of multi-variable objective function for both platform placement and task planning. It also discusses the implementation of the down-hill simplex algorithm, and some data from our initial investigation.


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