EDHMoR: Evolutionary designer of heterogeneous modular robots

Faina, Andres; Bellas, Francisco; Peña, Fernando López; Duro, Richard J.

doi:10.1016/j.engappai.2013.09.009

Cited by 46 publications

(49 citation statements)

References 20 publications

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“…Then the resulting robots are implemented physically to prove feasibility. The results were promising when applied to solve a linear motion problem but needed improvements in the case of static problems [5].…”

Section: Modular Roboticsmentioning

confidence: 93%

“…Modular self-reconfigurable robots involve various modules that can combine themselves autonomously into meta-modules that are capable of performing various tasks under different circumstances [5]. The ability to self-reconfigure allows these robots of metamorphosis, which in turn makes them capable of performing different sorts of kinematics.…”

Section: Self-reconfigurationmentioning

confidence: 99%

“…Each module involves actuators, sensors, computational, and communicational capabilities. Usually, these systems are homogeneous where all the modules are identical; however, there could be heterogeneous systems that contain different modules to maximize versatility [5].…”

Section: Modular Roboticsmentioning

confidence: 99%

“…In robotics, evolution has been proposed as a nature inspired approach to avoid the bias and limitations introduced by human designers and to produce better adapted robots to the environmental changes [5]. Simply, evolutionary robotics is a method of creating autonomous robots automatically without human intervention [6].…”

Section: Evolutionary Roboticsmentioning

confidence: 99%

“…However, an obvious constraint was the manufacturability of the resulting solutions. Therefore, Faíña et al proposed the use of modular robots as the fundamental building blocks for evolutionary processes because modularity allows building a wide variety of robotic structures, simplifies the search space, and ensures easy implementation in reality [5].…”

Section: Evolutionary Roboticsmentioning

confidence: 99%

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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: Modular Roboticsmentioning

confidence: 93%

Section: Self-reconfigurationmentioning

confidence: 99%

Section: Modular Roboticsmentioning

confidence: 99%

Section: Evolutionary Roboticsmentioning

confidence: 99%

Section: Evolutionary Roboticsmentioning

confidence: 99%

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Evolutionary Modular Robotics: Survey and Analysis

Alattas

Patel

Sobh

2018

J Intell Robot Syst

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Hybrid Wireless–Local Communication via Information Propagation for Modular Robotic Synchronization Applications

Holdcroft

Belke

Sigrist

et al. 2022

Advanced Intelligent Systems

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Modular robots (MRs) are a collection of individual robotic components which interlock in order to construct a full robot. [1] By adjusting the way in which these components connect, a robot can change topology to best suit the environment or task at hand. This adaptability poses advantages over traditional robots, as they can modify their underlying structure to improve performance or achieve tasks which otherwise would be impossible. MRs are particularly useful where the environment or task space is either unknown or very large, which includes disaster recovery, [2] space, [3,4] adaptive furniture, [5] structures, [6] tooling, [7] and education. [8] Failure due to scalability in numbers is a fundamental issue for MRs. Most experimental MRs run with less than 30 modules at a time, such as those listed in Table 1. If an element within a module fails 1% of the time, then one out of 30 modules will statistically fail during 26% of trials. [9] If there is no redundancy in place, the entire robot could fail. Many simulations run with hundreds of modules. [10] If MRs are to have hundreds modules with any sort of stability, then there must be a high degree of redundancy to account for failures. Synchronization of modules is critical. If a module acts out of synchronization with the others, not only will the robot fail to perform tasks properly, but its behavior may be self-destructive through self-collision. Communication therefore is a fundamental topic in MRs, where most robots opt for a combination of different types according to their speciality. Global communication spans the whole robot, while local communication acts just between neighboring modules. Local is necessary for configuration discovery and synchronization between neighbors. If the configuration is known and has a small number of modules, global communication eliminates the need for local communication, but most MRs opt for a combined solution to avoid overloading a single system, as shown in Table 1.The current trend for global communication is toward wireless. [11] Wireless communication allows for MRs to easily synchronize across all modules and interface with an external controller, but suffers from interference and packet loss with many clients. [9] Wireless systems consume far more power than local communication and are enough to negatively impact the performance of a robot. Lastly, there is another trend toward incorporating specialized modules with elements such as wireless cameras and other specific sensors. [10] These data-heavy devices will significantly impact the reliability of the networks with a high number of clients.

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