Task based design of modular robot manipulator using efficient genetic algorithm

Chung, Weon Kuu; Han, Jeongheon; Youm, Y.; Kim, S.H.

doi:10.1109/robot.1997.620087

Cited by 46 publications

(18 citation statements)

References 9 publications

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“…This algorithm has been implemented on physical robots. This work considers only the first level of modular architecture; which is kinematics synthesis [18].…”

Section: Modular Roboticsmentioning

confidence: 99%

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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“…This algorithm has been implemented on physical robots. This work considers only the first level of modular architecture; which is kinematics synthesis [18].…”

Section: Modular Roboticsmentioning

confidence: 99%

Evolutionary Modular Robotics: Survey and Analysis

Alattas

Patel

Sobh

2018

J Intell Robot Syst

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“…SGAs possess flaws, to achieve faster convergence, they have been modified to include elitism and tournament selection [33]. SGAs were used for morphology development in [50,56,63,66,74,83,84] and they were amended with elitism, or other selection methods [35,38,43,45,46,48,51,68,87,88]. A GA with novelty search and an objective based GA found application in [70] where individuals that performed differently were rewarded if they possessed novelty.…”

Section: Different Eas Appliedmentioning

confidence: 99%

A survey on evolutionary-aided design in robotics

Prabhu¹,

Seals²,

Kyberd³

et al. 2018

Robotica

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SUMMARYThe evolutionary-aided design process is a method to find solutions to design and optimisation problems. Evolutionary algorithms (EAs) are applied to search for optimal solutions from a solution space that evolves over several generations. EAs have found applications in many areas of robotics. This paper covers the efforts to determine body morphology of robots through evolution and body morphology with the controller of robots or similar creatures through co-evolution. The works are reviewed from the perspective of how different algorithms are applied and includes a brief explanation of how they are implemented.

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“…The solution of the upper level is used as an input to the lower level genetic algorithm. During the same time, (Chung et al 1997) worked for the optimal determination of link lengths of modular manipulators by using genetic algorithm. The evolutionary approach had also been applied to evolve the different 2D/3D morphologies using LEGO (Funes & Pollack 1998 components.…”

Section: Evolutionary Robotics Designmentioning

confidence: 99%

Evolutionary robotics in two decades: A review

Gupta

Singla

2015

Sadhana

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Evolutionary robotics (ER) has emerged as a fast growing field in the last two decades and has earned the attention of a number of researchers. Principles of biological evolution are applied in the form of evolutionary techniques for solving the complicated problems in the areas of robotic design and control. The diversity and the intensity of this growing field is presented in this paper through the contributions made by several researchers in the categories of robot controller design, robot body design, co-evolution of body and brain and in transforming the evolved robots in physical reality. The paper discusses some of the recent achievements in each of these fields along with some expected applications which are likely to motivate the future research. For the quick reference of the readers, a digest of all the works is presented in the paper, spanning the years and the areas of the research contributions.

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Task based design of modular robot manipulator using efficient genetic algorithm

Cited by 46 publications

References 9 publications

Evolutionary Modular Robotics: Survey and Analysis

Evolutionary Modular Robotics: Survey and Analysis

A survey on evolutionary-aided design in robotics

Evolutionary robotics in two decades: A review

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