WOSPP - A Wave Oriented Swarm Programming Paradigm

Thenius, Ronald; Varughese, Joshua Cherian; Moser, Daniel; Schmickl, Thomas

doi:10.1016/j.ifacol.2018.03.065

Cited by 6 publications

(8 citation statements)

References 8 publications

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“…We present both numerical simulation and robotic experiments to validate the presented method. Furthermore, this algorithm can be embedded into the swarm design paradigm WOSP (Thenius et al, 2018), a framework for controlling swarms utilizing the communication mechanism we briefly introduce in section 4.1. In section 4.2., we present the algorithm and its implementation.…”

Section: Related Workmentioning

confidence: 99%

“…The CIMAX algorithm enables a swarm of individuals with limited communication abilities to collectively determine which direction yields the maximum increase in information accessible to the collective. The fundamental communication mechanism presented here is inspired by slime mold ( dictyostelium discoideum ) and fireflies ( lampyridae ) and has previously been used to design various algorithms (Thenius et al, 2018; Varughese et al, 2016).…”

Section: The Cimax Algorithmmentioning

confidence: 99%

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CIMAX: collective information maximization in robotic swarms using local communication

et al. 2020

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Robotic swarms and mobile sensor networks are used for environmental monitoring in various domains and areas of operation. Especially in otherwise inaccessible environments, decentralized robotic swarms can be advantageous due to their high spatial resolution of measurements and resilience to failure of individuals in the swarm. However, such robotic swarms might need to be able to compensate misplacement during deployment or adapt to dynamical changes in the environment. Reaching a collective decision in a swarm with limited communication abilities without a central entity serving as decision-maker can be a challenging task. Here, we present the CIMAX algorithm for collective decision-making for maximizing the information gathered by the swarm as a whole. Agents negotiate based on their individual sensor readings and ultimately make a decision for collectively moving in a particular direction so that the swarm as a whole increases the amount of relevant measurements and thus accessible information. We use both simulation and real robotic experiments for presenting, testing, and validating our algorithm. CIMAX is designed to be used in underwater swarm robots for troubleshooting an oxygen depletion phenomenon known as “anoxia.”

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Section: Related Workmentioning

confidence: 99%

Section: The Cimax Algorithmmentioning

confidence: 99%

CIMAX: collective information maximization in robotic swarms using local communication

et al. 2020

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“…The internal timer with a defined periodicity is analogous to timer like behavior found in fireflies (Buck and Buck (1966), Camazine et al (2001)). Further details of this bio-inspired communication method are explained in Thenius et al (2018b).…”

Section: The Algorithmmentioning

confidence: 99%

Collective Event Detection Using Bio-inspired Minimalistic Communication in a Swarm of Underwater Robots

Varughese¹,

Hornischer²,

Thenius³

et al. 2019

The 2019 Conference on Artificial Life

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Mobile sensor networks and robotic swarms are being used for monitoring and exploring environments or environmental events due to the advantages offered by their distributed nature. However, coordination and self-organization of a large number of individuals is often costly in terms of energy and computation power, thus limiting the longevity of the distributed system. In this paper we present a bio-inspired algorithm enabling a robotic swarm to collectively detect anomalies in environmental parameters in a self-organized, reliable and energy efficient manner. Individuals in the swarm communicate via 1-bit signals to collectively confirm the detection of an anomaly while minimizing energy spent for communication and taking measurements. This algorithm is specifically designed for a swarm of underwater robots called "aMussels" to examine a phenomenon referred to as "anoxia" which results in oxygen depletion in the lagoon of Venice. We present the algorithm, conduct simulations and robotic experiments to examine the performance of the algorithm with respect to early detection of anoxia while minimizing energy consumption.

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“…The CIMAX algorithm enables a swarm of individuals with limited communication abilities to make a collective decision regarding its direction of motion in order to maximize the information accessible to the collective. The fundamental communication mechanism presented here is inspired by slime mold (dictyostelium discoideum) and fireflies (lampyridae) and has previously been used to design various algorithms (Varughese et al, 2016;Thenius et al, 2018). Thenius et al (2018) unified various swarm behaviours into one general framework called "wave oriented swarm programming paradigm" or WOSPP.…”

Section: The Cimax Algorithmmentioning

confidence: 99%

“…We present both numerical simulation and robotic experiments to validate the presented method. Furthermore, this algorithm can be embedded into the "wave oriented swarm programming paradigm" (WOSPP) (Thenius et al, 2018), a framework for controlling swarms using the communication mechanism we briefly introduce in Section 2. In Section 2.2 we present the algorithm and its implementation.…”

Section: Introductionmentioning

confidence: 99%

CIMAX: Collective Information Maximization in Robotic Swarms Using Local Communication

Hornischer¹,

Varughese²,

Thenius³

et al. 2019

Preprint

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Robotic swarms and mobile sensor networks are used for environmental monitoring in various domains and areas of operation. Especially in otherwise inaccessible environments decentralized robotic swarms can be advantageous due to their high spatial resolution of measurements and resilience to failure of individuals in the swarm. However, such robotic swarms might need to be able to compensate misplacement during deployment or adapt to dynamical changes in the environment. Reaching a collective decision in a swarm with limited communication abilities without a central entity serving as decision-maker can be a challenging task. Here we present the CIMAX algorithm for collective decision making for maximizing the information gathered by the swarm as a whole. Agents negotiate based on their individual sensor readings and ultimately make a decision for collectively moving in a particular direction so that the swarm as a whole increases the amount of relevant measurements and thus accessible information. We use both simulation and real robotic experiments for presenting, testing and validating our algorithm. CIMAX is designed to be used in underwater swarm robots for troubleshooting an oxygen depletion phenomenon known as "anoxia".

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WOSPP - A Wave Oriented Swarm Programming Paradigm

Cited by 6 publications

References 8 publications

CIMAX: collective information maximization in robotic swarms using local communication

CIMAX: collective information maximization in robotic swarms using local communication

Collective Event Detection Using Bio-inspired Minimalistic Communication in a Swarm of Underwater Robots

CIMAX: Collective Information Maximization in Robotic Swarms Using Local Communication

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