Symbiotic robot organisms

Kernbach, Serge; Meister, Eugen; Schlachter, Florian; Jebens, Kristof; Szymanski, Marc; Liedke, Jens; Laneri, Davide; Winkler, Lutz; Schmickl, Thomas; Thenius, Ronald; Corradi, Paolo; Ricotti, Leonardo

doi:10.1145/1774674.1774685

Cited by 62 publications

(7 citation statements)

References 9 publications

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“…The Termes robots are block-carrying climbing robots that can create these structures in unstructured environments. Symbrion and Replicator (Kernbach et al, 2008) are two sister projects, that develop autonomous platforms for usage in swarms. They can be operated either individually or form special patterns by physically connecting to each other.…”

Section: Terrestrialmentioning

confidence: 99%

Swarm Robotic Behaviors and Current Applications

et al. 2020

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In swarm robotics multiple robots collectively solve problems by forming advantageous structures and behaviors similar to the ones observed in natural systems, such as swarms of bees, birds, or fish. However, the step to industrial applications has not yet been made successfully. Literature is light on real-world swarm applications that apply actual swarm algorithms. Typically, only parts of swarm algorithms are used which we refer to as basic swarm behaviors. In this paper we collect and categorize these behaviors into spatial organization, navigation, decision making, and miscellaneous. This taxonomy is then applied to categorize a number of existing swarm robotic applications from research and industrial domains. Along with the classification, we give a comprehensive overview of research platforms that can be used for testing and evaluating swarm behavior, systems that are already on the market, and projects that target a specific market. Results from this survey show that swarm robotic applications are still rare today. Many industrial projects still rely on centralized control, and even though a solution with multiple robots is employed, the principal idea of swarm robotics of distributed decision making is neglected. We identified mainly following reasons: First of all, swarm behavior emerging from local interactions is hard to predict and a proof of its eligibility for applications in an industrial context is difficult to provide. Second, current communication architectures often do not match requirements for swarm communication, which often leads to a system with a centralized communication infrastructure. Finally, testing swarms for real industrial applications is an issue, since deployment in a productive environment is typically too risky and simulations of a target system may not be sufficiently accurate. In contrast, the research platforms present a means for transforming swarm robotics solutions from theory to prototype industrial systems.

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Section: Terrestrialmentioning

confidence: 99%

Swarm Robotic Behaviors and Current Applications

et al. 2020

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“…It also helps by guiding others in the assembly to traverse a desired path. Additionally, a self-assembly is generally more robust because of the combined capabilities of heterogeneous robotic modules (Kernbach et al 2008;Dorigo et al 2013;Trianni et al 2014;Dorigo et al 2004).…”

Section: Swarm Roboticsmentioning

confidence: 99%

Reconfigurable swarm robots for structural health monitoring: a brief review

Jahanshahi

Shen

Mondal

et al. 2017

Int J Intell Robot Appl

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Autonomous monitoring of infrastructure systems offers a promising alternative to manual inspection techniques which are mostly tedious, expensive and prone to error. Robot-based autonomous monitoring systems not only provide higher precision, but they also allow frequent inspection of infrastructure systems at a much lower cost. Recent advancements in robotic systems have led to the development of reconfigurable swarm robots (RSR) that can change their shape and functionality dynamically, without any external intervention. RSR have the advantages of being modular, on-site reconfigurable, multifunctional, incrementally assemble-able, reusable, faulttolerant, and even repairable on the orbit. Newly-developed reconfigurable robots are expected to bring a radical change in the prevailing structural health monitoring techniques, thus augmenting the efficiency, accuracy and affordability of inspection operations. This paper presents a holistic review of the previous studies and state-of-the-art technologies in the field of RSR, and argues that RSR offer great potential advantages from the perspective of monitoring and assessment of civil and mechanical systems. A roadmap for future research has also been outlined based on the limitations of the current methods and anticipated needs of future inspection systems.

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“…The chapter then briefly reviews the system design and features of couple of state-of-the-art re-configurable robotic platforms that support power sharing. It then introduces the design of a re-configurable robotic platform; namely REPLI-CATOR (Kernbach et al 2008). The proposed power management system with fault tolerant energy sharing is designed, developed and integrated in the electronic design of REPLICATOR robotic modules as a part of this research work.…”

Section: Organization Of the Bookmentioning

confidence: 99%

“…To gain such abilities, the idea behind heterogeneous platform design of REPLICATOR (Kernbach et al 2008) robotic modules was intended to ensure high reliability, self-reconfigurability and adaptability in a modular robotic organism. The three heterogeneous robotic platforms specialized in different features are designed by the REPLICATOR consortium, namely; Kabot, Scout robot and Active wheel.…”

Section: Replicatorsmentioning

confidence: 99%

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Self-Sufficiency of an Autonomous Reconfigurable Modular Robotic Organism

Qadir¹

2015

Adaptation, Learning, and Optimization

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The role of adaptation, learning and optimization are becoming increasingly essential and intertwined. The capability of a system to adapt either through modification of its physiological structure or via some revalidation process of internal mechanisms that directly dictate the response or behavior is crucial in many real world applications. Optimization lies at the heart of most machine learning approaches while learning and optimization are two primary means to effect adaptation in various forms. They usually involve computational processes incorporated within the system that trigger parametric updating and knowledge or model enhancement, giving rise to progressive improvement. This book series serves as a channel to consolidate work related to topics linked to adaptation, learning and optimization in systems and structures. Topics covered under this series include:• complex adaptive systems including evolutionary computation, memetic computing, swarm intelligence, neural networks, fuzzy systems, tabu search, simulated annealing, etc.

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Symbiotic robot organisms

Cited by 62 publications

References 9 publications

Swarm Robotic Behaviors and Current Applications

Swarm Robotic Behaviors and Current Applications

Reconfigurable swarm robots for structural health monitoring: a brief review

Self-Sufficiency of an Autonomous Reconfigurable Modular Robotic Organism

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