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Research Papers

Optimal Distribution of Active Modules in Reconfiguration Planning of Modular Robots

[+] Author and Article Information
Meibao Yao

Deep Space Exploration Research Center,
Harbin Institute of Technology,
Harbin 150001, China
e-mail: meibaoyao@gmail.com

Xueming Xiao

School of Opto-Electronic Engineering,
Changchun University of
Science and Technology,
Changchun 130022, China
e-mail: alexcapshow@gmail.com

Christoph H. Belke

Reconfigurable Robotics Lab,
École Polytechnique Fédérale de Lausanne,
Lausanne 1015, Switzerland
e-mail: christoph.belke@epfl.ch

Hutao Cui

Deep Space Exploration Research Center,
Harbin Institute of Technology,
Harbin 150001, China
e-mail: cuiht@hit.edu.cn

Jamie Paik

Reconfigurable Robotics Lab,
École Polytechnique Fédérale de Lausanne,
Lausanne 1015, Switzerland
e-mail: jamie.paik@epfl.ch

1Corresponding author.

Contributed by the Mechanisms and Robotics Committee of ASME for publication in the JOURNAL OF MECHANISMS AND ROBOTICS. Manuscript received March 31, 2018; final manuscript received November 5, 2018; published online December 17, 2018. Assoc. Editor: Robert J. Wood.

J. Mechanisms Robotics 11(1), 011017 (Dec 17, 2018) (9 pages) Paper No: JMR-18-1092; doi: 10.1115/1.4041972 History: Received March 31, 2018; Revised November 05, 2018

Reconfigurability in versatile systems of modular robots is achieved by appropriately actuating individual modular units. Optimizing the distribution of active and passive modules in modular architecture can significantly reduce both cost and energy of a reconfiguration task. This paper presents a methodology for planning this distribution in modular robots, resulting in a minimum number of active modules that guarantees the capability to reconfigure. We discuss the optimal distribution problem in layout-based and target-based planning schemes such that modular robots can instantly respond to reconfiguration commands with either an initial planar layout or a target configuration as input. We propose heuristic algorithms as solutions for the different scenarios, which we demonstrate by applying them to Mori, a modular origami robot, in simulation. The results show that our algorithms yield high-quality distribution schemes in reduced time, and are thus viable for real-time applications in modular robotic systems.

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Figures

Grahic Jump Location
Fig. 1

An overview of our method for planning distribution of active modules in modular robots

Grahic Jump Location
Fig. 2

The reconfiguration procedure of the Mori robotic platform: (a) an initial layout is shaped when each triangular module connects to other modular units, (b) the aggregates are actuated with a controlled sequence of modules to perform folding motion during the reconfiguration (robotic motion), and (c) the desired 3D configuration of a quadruped comes into conformation

Grahic Jump Location
Fig. 3

An initial layout resulting in two feasible 3D shapes, a boat and a quadruped, using the layout-based planner. A simplified actuation sequence is shown for each 3D shape.

Grahic Jump Location
Fig. 4

Four initial layouts with two distribution schemes each, generated by two layout-based planning algorithms

Grahic Jump Location
Fig. 5

Computational efficiency of the layout-based algorithm compared to the k-coloring approach

Grahic Jump Location
Fig. 6

Two 3D shapes with three initial layouts each, generated by the target-based approach, one of which is optimal: (a) an octahedron and (b) a quadruped

Grahic Jump Location
Fig. 7

A scalable tetrahedron, its optimal initial layout, and the distribution of active modules

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