Design of the ATRON lattice-based self-reconfigurable robot

Østergaard, Esben Hallundbæk; Kassow, Kristian; Beck, Richard; Lund, Henrik Hautop

doi:10.1007/s10514-006-8546-1

Cited by 171 publications

(107 citation statements)

References 22 publications

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“…Lattice-type systems exploit lattice regularity when aligning connectors during self-reconfiguration in order to allow faster and easier self-reconfiguration. However, assuming that all modules conform to the lattice can be problematic for systems with a big number of modules [30]. One example of a lattice-based self-reconfigurable robot is M-TRAN [31,32].…”

Section: Self-reconfigurationmentioning

confidence: 99%

“…Østergaard and Lund explored evolving controllers of M-TRAN [41] and ATRON [30] selfreconfigurable modular robotic systems in simulation. Employing Genetic Algorithm for implementing M-TRAN walking behavior is very complicated because evolving each controller locally to generate a global behavior is affected by the conditions of neighboring modules.…”

Section: Self-reconfigurationmentioning

confidence: 99%

“…Therefore, when attempting to evolve ATRON controllers individually to allow the modular collection of moving in the right direction, two modules were evaluated as a couple instead of evaluating single modules using competitive co-evolution and symbiotic co-evolution. This work did not address the constraints of physical systems [30].…”

Section: Self-reconfigurationmentioning

confidence: 99%

See 2 more Smart Citations

Evolutionary Modular Robotics: Survey and Analysis

Alattas

Patel

Sobh

2018

J Intell Robot Syst

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This paper surveys various applications of artificial evolution in the field of modular robots. Evolutionary robotics aims to design autonomous adaptive robots automatically that can evolve to accomplish a specific task while adapting to environmental changes. A number of studies have demonstrated the feasibility of evolutionary algorithms for generating robotic control and morphology. However, a huge challenge faced was how to manufacture these robots. Therefore, modular robots were employed to simplify robotic evolution and their implementation in real hardware. Consequently, more research work has emerged on using evolutionary computation to design modular robots rather than using traditional hand design approaches in order to avoid cognition bias. These techniques have the potential of developing adaptive robots that can achieve tasks not fully understood by human designers. Furthermore, evolutionary algorithms were studied to generate global modular robotic behaviors including; self-assembly, self-reconfiguration, self-repair, and self-reproduction. These characteristics allow modular robots to explore unstructured and hazardous environments. In order to accomplish the aforementioned evolutionary modular robotic promises, this paper reviews current research on evolutionary robotics and modular robots. The motivation behind this work is to identify the most promising methods that can lead to developing autonomous adaptive robotic systems that require the minimum task related knowledge on the designer side.

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Section: Self-reconfigurationmentioning

confidence: 99%

Section: Self-reconfigurationmentioning

confidence: 99%

Section: Self-reconfigurationmentioning

confidence: 99%

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Evolutionary Modular Robotics: Survey and Analysis

Alattas

Patel

Sobh

2018

J Intell Robot Syst

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“…Distributed control of ATRON modular robots [5] which are supposed to perform a locomotion task is investigated here. Three different morphological configurations of the robot are used as experimental case studies.…”

Section: Introductionmentioning

confidence: 99%

Fractal Gene Regulatory Networks for Robust Locomotion Control of Modular Robots

Zahadat

Christensen

Schultz

et al. 2010

From Animals to Animats 11

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Abstract. Designing controllers for modular robots is difficult due to the distributed and dynamic nature of the robots. In this paper fractal gene regulatory networks are evolved to control modular robots in a distributed way. Experiments with different morphologies of modular robot are performed and the results show good performance compared to previous results achieved using learning methods. Furthermore, some experiments are performed to investigate evolvability of the achieved solutions in the case of module failure and it is shown that the system is capable of come up with new effective solutions.

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“…In this way a number of many relative simple modules can be connected to form a sophisticated robot. A comprehensive overview of the different existing modular robot systems can be found in Chapter 4 of [12].…”

Section: Introductionmentioning

confidence: 99%

R-Charon, a Modeling Language for Reconfigurable Hybrid Systems

Kratz

Sokolsky

Pappas

et al. 2006

Hybrid Systems: Computation and Control

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This paper describes the modeling language as an extension for architectural reconfiguration to the existing distributed hybrid system modeling language Charon. The target application domain of R-Charon includes but is not limited to modular reconfigurable robots and large-scale transportation systems. While largely leaving the Charon syntax and semantics intact, R-Charon allows dynamic creation and destruction of components (agents) as well as of links (references) between the agents. As such, R-Charon is the first formal, hybrid automata based modeling language which also addresses dynamic reconfiguration. We develop and present the syntax and operational semantics for R-Charon on three levels: behavior (modes), structure (agents) and configuration (system). Abstract. This paper describes the modeling language R-Charon as an extension for architectural reconfiguration to the existing distributed hybrid system modeling language Charon. The target application domain of R-Charon includes but is not limited to modular reconfigurable robots and large-scale transportation systems. While largely leaving the Charon syntax and semantics intact, R-Charon allows dynamic creation and destruction of components (agents) as well as of links (references) between the agents. As such, R-Charon is the first formal, hybrid automata based modeling language which also addresses dynamic reconfiguration. We develop and present the syntax and operational semantics for R-Charon on three levels: behavior (modes), structure (agents) and configuration (system).

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Design of the ATRON lattice-based self-reconfigurable robot

Cited by 171 publications

References 22 publications

Evolutionary Modular Robotics: Survey and Analysis

Evolutionary Modular Robotics: Survey and Analysis

Fractal Gene Regulatory Networks for Robust Locomotion Control of Modular Robots

R-Charon, a Modeling Language for Reconfigurable Hybrid Systems

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