Algorithms for fast concurrent reconfiguration of hexagonal metamorphic robots

Walter, Jennifer E.; Tsai, E.M.; Amato, Nancy M.

doi:10.1109/tro.2004.842325

Cited by 33 publications

(31 citation statements)

References 19 publications

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“…Researchers have attempted to optimize the path planning process when reconfiguring sets of connected modules [18,2]. Others have focused on encoding a desired shape in a set of rules that is executed by each module [9].…”

Section: Related Workmentioning

confidence: 99%

What's in the Bag: A Distributed Approach to 3D Shape Duplication with Modular Robots

Gilpin¹,

Rus²

2012

Robotics: Science and Systems VIII

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Abstract-Our goal is to develop an automated digital fabrication process that can make any object out of smart materials. In this paper, we present an algorithm for creating shapes by the process of duplication, using modules we have termed smart sand. The object to be duplicated is dipped into a bag of smart sand; the particles exchange messages to sense the object's shape; and then the particles selectively form mechanical bonds with their neighbors to form a duplicate of the original.Our algorithm is capable of duplicating convex and concave 3D objects in a completely distributed manner. It uses O(1) storage space and O(n) inter-module messages per module. We perform close to 500 experiments using a realistic simulator with over 1400 modules. These experiments confirm the functionality and messaging demands of our distributed duplication algorithm while demonstrating that the algorithm can be used to form interesting and useful shapes.

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Section: Related Workmentioning

confidence: 99%

What's in the Bag: A Distributed Approach to 3D Shape Duplication with Modular Robots

Gilpin¹,

Rus²

2012

Robotics: Science and Systems VIII

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“…Walter et. al [12] initially find all admissible paths for reconfiguration and heuristically ranks them. In the second stage, a deterministic, distributed algorithm is used to achieve reconfiguration using little intermodule message passing.…”

Section: Related Workmentioning

confidence: 99%

Hierarchical Motion Planning for Self-reconfigurable Modular Robots

Bhat

Kuffner

Goldstein

et al. 2006

2006 IEEE/RSJ International Conference on Intelligent Robots and Systems

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Abstract-Motion planning for a self-reconfigurable robot involves coordinating the movement and connectivity of each of its homogeneous modules. Reconfiguration occurs when the shape of the robot changes from some initial configuration to a target configuration. Finding an optimal solution to reconfiguration problems involves searching the space of possible robot configurations. As this space grows exponentially with the number of modules, optimal planning becomes intractable. We propose a hierarchical planning approach that computes heuristic global reconfiguration strategies efficiently. Our approach consists of a base planner that computes an optimal solution for a few modules and a hierarchical planner that calls this base planner or reuses pre-computed plans at each level of the hierarchy to ultimately compute a global suboptimal solution. We present results from a prototype implementation of the method that efficiently plans for self-reconfigurable robots with several thousand modules. We also discuss tradeoffs and performance issues including scalability, heuristics and plan optimality.

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“…This global-centralized to local-decentralized control model has been widely used. [20][21][22][23] While allowing large collections of independent modules to form determinate shapes, local rules in each module must be adjusted for each new global structure, which increases the burden of communication and is not practical for physical modules working in real word.…”

Section: Introductionmentioning

confidence: 99%

Modeling the fractal development of modular robots

Bie

Liu

Zhao

et al. 2017

Advances in Mechanical Engineering

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Modeling and controlling self-reconfiguration of modular robots is still a challenging problem in the field of distributed control. The two main constrains are the design of target shapes and the absence of global state for decentralized modules. We present a new way for those two problems inspired from the developmental process of plant growth. As a mathematical theory of plant development, L-systems capture the essence of growth process. We extend L-systems to the self-reconfiguration process of modules robots. Target configurations will be described in a string of symbols, and robotic structures capture fractal characters through the rewriting function. Extended graphical interpretation of Lsystem symbols can generate module-level predictions about robotic global states. Simulations of different selfreconfiguration processes illustrate the proposed method.

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Algorithms for fast concurrent reconfiguration of hexagonal metamorphic robots

Cited by 33 publications

References 19 publications

What's in the Bag: A Distributed Approach to 3D Shape Duplication with Modular Robots

What's in the Bag: A Distributed Approach to 3D Shape Duplication with Modular Robots

Hierarchical Motion Planning for Self-reconfigurable Modular Robots

Modeling the fractal development of modular robots

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