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Center-configuration selection technique for the reconfigurable modular robot

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Science in China Series F: Information Sciences Aims and scope Submit manuscript

Abstract

The reconfigurable modular robot has an enormous amount of configurations to adapt to various environments and tasks. It greatly increases the complexity of configuration research in that the possible configuration number of the reconfigurable modular robot grows exponentially with the increase of module number. Being the initial configuration or the basic configuration of the reconfigurable robot, the center-configuration plays a crucial role in system’s actual applications. In this paper, a novel center-configuration selection technique has been proposed for reconfigurable modular robots. Based on the similarities between configurations’ transformation and graph theory, configuration network has been applied in the modeling and analyzing of these configurations. Configuration adjacency matrix, reconfirmation cost matrix, and center-configuration coefficient have been defined for the configuration network correspondingly. Being similar to the center-location problem, the center configuration has been selected according to the largest center-configuration coefficient. As an example of the reconfigurable robotic system, AMOEBA-I, a three-module reconfigurable robot with nine configurations which was developed in Shenyang Institute of Automation (SIA), Chinese Academy of Sciences (CAS), has been introduced briefly. According to the numerical simulation result, the center-configuration coefficients for these nine configurations have been calculated and compared to validate this technique. Lastly, a center-configuration selection example is provided with consideration of the adjacent configurations. The center-configuration selection technique proposed in this paper is also available to other reconfigurable modular robots.

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Author information

Authors and Affiliations

  1. Robotics Laboratory of Chinese Academy of Sciences, Shenyang Institute of Automation, Shenyang, 110016, China

    Liu JinGuo, Wang YueChao, Li Bin, Ma ShuGen & Tan DaLong

  2. COE Research Institute, Ritsumeikan University, Shiga-ken, 525-8577, Japan

    Liu JinGuo

  3. Graduate School of Chinese Academy of Sciences, Beijing, 100049, China

    Ma ShuGen

Authors
  1. Liu JinGuo

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  2. Wang YueChao

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  3. Li Bin

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  4. Ma ShuGen

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  5. Tan DaLong

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Corresponding author

Correspondence toLiu JinGuo.

Additional information

Supported in part by the National High-Technology 863 Program (Grant No. 2001AA422360), the Chinese Academy of Sciences Advanced Manufacturing Technology R&D Base Fund (Grant Nos. A050104 and F050108), and the GUCAS-BHP Billiton Scholarship

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