Self-Reconfigurable Modular Robot M-TRAN: Distributed Control and Communication

Kurokawa, Haruhisa; Tomita, Kohji; Kamimura, Akiya; Kokaji, Shigeru; Hasuo, Takashi; Murata, Satoshi

doi:10.4108/icst.robocomm2007.2119

Cited by 26 publications

(15 citation statements)

References 11 publications

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“…An M-TRAN atom [7] consists of two identical elements connected by a link. An element can be viewed as a half cube glued to a half cylinder, as depicted in Fig.…”

Section: A M-tran and Molecube Atomsmentioning

confidence: 99%

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Efficient reconfiguration of lattice-based modular robots

Aloupis

Benbernou

Damian

et al. 2013

Computational Geometry

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Abstract-Modular robots consist of many small units that attach together and can perform local motions. By combining these motions, we can achieve a reconfiguration of the global shape. The term modular comes from the idea of grouping together a fixed number of units into a module, which behaves as a larger individual component.Recently, a fair amount of research has focused on Crystalline robots, whose units (and modules) fit on a cubic lattice. When the proper module size is formed, these robots can reconfigure in linear time within a rather physically restrictive model, or in O(log n) time in a more unrestricted theoretical model.In this paper, we show that the results for Crystalline robots also apply to two other modular robots: M-TRAN and Molecube. The common requirement, for each robot type, is that a fixed number of units combine to create modules of specified shapes. In this way, we are able to simulate the actions of Crystalline modules. Previous reconfiguration bounds thus transfer automatically, as long as the robots are composed of the module shapes that we specify.

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“…An M-TRAN atom [7] consists of two identical elements connected by a link. An element can be viewed as a half cube glued to a half cylinder, as depicted in Fig.…”

Section: A M-tran and Molecube Atomsmentioning

confidence: 99%

“…As far as we know, similar bounds for other lattice-based modular robots such as Molecube [15] and M-TRAN [7] are not yet known. In fact, we believe that most modular robots are capable of the same theoretical bounds, given an appropriate module design.…”

Section: Introductionmentioning

confidence: 98%

Efficient reconfiguration of lattice-based modular robots

Aloupis

Benbernou

Damian

et al. 2013

Computational Geometry

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“…Other modular robots: It has been shown [Aloupis et al, 2009a] that suitably constructed modules of other prototypes (e.g., M-TRAN [Kurokawa et al, 2007], ATRON [Jørgensen et al, 2004]) are capable of simulating Crystalline atoms. Such modules may require 50-100 atoms to simulate one Crystalline atom, and the resulting shape is not compact.…”

Section: Observationsmentioning

confidence: 99%

Efficient constant-velocity reconfiguration of crystalline robots

Aloupis¹,

Collette²,

Damian³

et al. 2011

Robotica

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Abstract:In this paper we propose novel algorithms for reconfiguring modular robots that are composed of n atoms. Each atom has the shape of a unit cube and can expand/contract each face by half a unit, as well as attach to or detach from faces of neighboring atoms. For universal reconfiguration, atoms must be arranged in 2×2×2 modules. We respect certain physical constraints: each atom reaches at most constant velocity and can displace at most a constant number of other atoms. We assume that one of the atoms has access to the coordinates of atoms in the target configuration.Our algorithms involve a total of O(n 2 ) atom operations, which are performed in O(n) parallel steps.This improves on previous reconfiguration algorithms, which either use O(n 2 ) parallel steps [Rus and Vona, 2001, Vassilvitskii et al., 2002, Butler and Rus, 2003 or do not respect the constraints mentioned above [Aloupis et al., 2009b]. In fact, in the setting considered, our algorithms are optimal. A further advantage of our algorithms is that reconfiguration can take place within the union of the source and target configuration space, and only requires local communication.

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“…SRR was first proposed by Fukuda, i.e., the CEBOT [1]. Since the initial conception, many other SRR systems, including Roombot [2][3][4], M-Cube [5], M-TRAN [6][7][8][9][10], ModRED [11], SuperBot [12][13][14] and Yamor [15][16][17], to name only a few, have been developed. Current docking algorithms are based on either infrared sensing or vision.…”

Section: Introductionmentioning

confidence: 99%

A Multi-Sensory Autonomous Docking Approach for a Self-Reconfigurable Robot without Mechanical Guidance

Zhu

Jin

Zhang

et al. 2014

International Journal of Advanced Robotic Systems

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The most important feature of a Self-Reconfigurable Robot (SRR) is that it is reconfigurable and self-repairing. At the centre of these capabilities is autonomous docking. One difficulty for docking is the alignment between two robots. Current strategies overcome this by integrating a mechanical guiding device within the connecting mechanism. This increases the robustness of docking but compromises the flexibility of reconfiguration. In this paper, we present a new autonomous docking strategy that can overcome the drawbacks of current approaches. The new strategy uses a novel hook-type connecting mechanism and multi-sensory guidance. The hook-type connecting mechanism is strong and rigid for reliable physical connection between the modules. The multisensory docking strategy, which includes visual-sensorguided rough positioning, Hall-sensor-guided fine positioning, and the locking between moving and target modules, guarantees robust docking without sacrificing reconfigurability. The proposed strategy is verified by docking between a worm-shaped robot and one target module, and docking among three moving robots to form a T-shaped configuration. The experimental results showed that the strategy is very effective.

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Self-Reconfigurable Modular Robot M-TRAN: Distributed Control and Communication

Cited by 26 publications

References 11 publications

Efficient reconfiguration of lattice-based modular robots

Efficient reconfiguration of lattice-based modular robots

Efficient constant-velocity reconfiguration of crystalline robots

A Multi-Sensory Autonomous Docking Approach for a Self-Reconfigurable Robot without Mechanical Guidance

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