Issues in Self-Repairing Robotic Self-Assembly

Arbuckle, D.; Requicha, Aristides A. G.

doi:10.1007/978-3-642-33902-8_6

Cited by 4 publications

(3 citation statements)

References 12 publications

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“…Using this approach, the pattern would slowly assemble. Similar strategies were studied by Smith et al (2009), Arbuckle and Requicha (2010), Arbuckle and Requicha (2012), Fox and Shamma (2015). In more recent work, Haghighat and Martinoli (2017) proposed an algorithm for the automatic encoding of such rules for rotationally symmetric modules.…”

Section: Review Of Approaches To Pattern Formation By a Swarm Of Robotsmentioning

confidence: 85%

Provable self-organizing pattern formation by a swarm of robots with limited knowledge

et al. 2019

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In this paper we present a procedure to automatically design and verify the local behavior of robots with highly limited cognition. All robots are: anonymous, homogeneous, noncommunicating, memoryless, reactive, do not know their global position, do not have global state information, and operate by a local clock. They only know: (1) the relative location of their neighbors within a short range and (2) a common direction (North). We have developed a procedure to generate a local behavior that allows the robots to self-organize into a desired global pattern despite their individual limitations. This is done while also avoiding collisions and keeping the coherence of the swarm at all times. The generated local behavior is a probabilistic local state-action map. The robots follow this stochastic policy to select an action based on their current perception of their neighborhood (i.e., their local state). It is this stochasticity, in fact, that allows the global pattern to eventually emerge. For a generated local behavior, we present a formal proof procedure to verify whether the desired pattern will always eventually emerge from the local actions of the agents. The novelty of the proof procedure is that it is primarily local in nature and focuses on the local states of the robots and the global implications of their local actions. A local approach is of interest to reduce the computational effort as much as possible when verifying the emergence of larger patterns. Finally, we show how the behavior could be implemented on real robots and investigate this with extensive simulations on a realistic robot model. To the best of our knowledge, no other solutions exist for robots with such limited cognition to achieve this level of coordination with proof that the desired global property will emerge.

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Section: Review Of Approaches To Pattern Formation By a Swarm Of Robotsmentioning

confidence: 85%

Provable self-organizing pattern formation by a swarm of robots with limited knowledge

et al. 2019

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“…Over time, the agents would latch into the final assembly. Other similar works include the work of Arbuckle and Requicha (2010), Arbuckle and Requicha (2012), Klavins (2007), Fox and Shamma (2015), and Haghighat and Martinoli (2017). These schemes assume that the agents can drift randomly in an enclosed area, and that by doing so they will eventually meet each other, at which point they will latch together.…”

Section: Related Work and Research Contextmentioning

confidence: 99%

Provable Emergent Pattern Formation by a Swarm of Anonymous, Homogeneous, Non-Communicating, Reactive Robots with Limited Relative Sensing and no Global Knowledge or Positioning

Coppola,

Guo,

Gill

et al. 2018

Preprint

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In this work, we explore emergent behaviors by swarms of anonymous, homogeneous, non-communicating, reactive robots that do not know their global position and have limited relative sensing. We introduce a novel method that enables such severely limited robots to autonomously arrange in a desired pattern and maintain it. The method includes an automatic proof procedure to check whether a given pattern will be achieved by the swarm from any initial configuration. An attractive feature of this proof procedure is that it is local in nature, avoiding as much as possible the computational explosion that can be expected with increasing robots, states, and action possibilities. Our approach is based on extracting the local states that constitute a global goal (in this case, a pattern). We then formally show that these local states can only coexist when the global desired pattern is achieved and that, until this occurs, there is always a sequence of actions that will lead from the current pattern to the desired pattern. Furthermore, we show that the agents will never perform actions that could a) lead to intra-swarm collisions or b) cause the swarm to separate. After an analysis of the performance of pattern formation in the discrete domain, we also test the system in continuous time and space simulations and reproduce the results using asynchronous agents operating in unbounded space. The agents successfully form the desired patterns while avoiding collisions and separation.

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“…ate collective responses to different tasks. Arbuckle and Requicha[44] (Fig. 2:6) propose active self-assembly, a specific approach for constructing arbitrary shapes with swarms of identical and identically programmed robots.…”

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confidence: 99%

A review of morphogenetic engineering

2013

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Generally, phenomena of spontaneous pattern formation are random and repetitive, whereas elaborate devices are the deterministic product of human design. Yet, biological organisms and collective insect constructions are exceptional examples of complex systems that are both architectured and self-organized. Can we understand their precise self-formation capabilities and integrate them with technological planning? Can physical systems be endowed with information, or informational systems be embedded in physics, to create autonomous morphologies and functions? To answer these questions, we have launched in 2009, and developed through a series of workshops and a collective book, a new field of research called Morphogenetic Engineering. It is the first initiative of its kind to rally and promote models and implementations of complex self-architecturing systems. Particular emphasis is set on the programmability and computational abilities of self-organization, properties that are often underappreciated in complex systems science-while, conversely, the benefits of self-organization are often underappreciated in engineering methodologies 1 .

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Issues in Self-Repairing Robotic Self-Assembly

Cited by 4 publications

References 12 publications

Provable self-organizing pattern formation by a swarm of robots with limited knowledge

Provable self-organizing pattern formation by a swarm of robots with limited knowledge

Provable Emergent Pattern Formation by a Swarm of Anonymous, Homogeneous, Non-Communicating, Reactive Robots with Limited Relative Sensing and no Global Knowledge or Positioning

A review of morphogenetic engineering

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