Probabilistic Modelling of a Bio-Inspired Collective Experiment with Real Robots

Martinoli, Alcherio; Mondada, Francesco

doi:10.1007/978-3-642-72198-4_28

Cited by 14 publications

(6 citation statements)

References 5 publications

(6 reference statements)

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“…Autonomy has been studied in bio-inspired [39] and decentralized peer-to-peer [40,41] approaches, which are particularly good at decomposing large or complex problems otherwise hard to tackle using standard centralized solutions. Autonomy also directly refers to intelligent and multi-agent systems [42] in general, where coordination and distributed problem planning/solving are tackled using distributed artificial intelligent techniques.…”

Section: Dynamics In Decentralized Settingsmentioning

confidence: 99%

Emergent Semantics Systems

Aberer

2004

Semantics of a Networked World. Semantics for Grid Databases

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Abstract. With new standards like RDF or OWL paving the way for the much anticipated Semantic Web, a new breed of very large scale semantic systems is about to appear. Traditional semantic reconciliation techniques, dependent upon shared vocabularies or global ontologies, cannot be used in such open and dynamic environments. Instead, new heuristics based on emerging properties and local consensuses have to be exploited in order to foster semantic interoperability in the large. In this paper, we outline the main differences between traditional semantic reconciliation methods and these new heuristics. Also, we characterize the resulting emergent semantics systems and provide a couple of hints vis-à-vis their potential applications.

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Section: Dynamics In Decentralized Settingsmentioning

confidence: 99%

Emergent Semantics Systems

Aberer

2004

Semantics of a Networked World. Semantics for Grid Databases

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“…The behavior of ant colonies has also inspired research in robotics, in particular for the design of distributed control algorithms for groups of robots [111]. An example of a task that has been used as a benchmark for ant algorithms applied to distributed robotics problems is cooperative box pushing [112].…”

Section: Algorithms Inspired By Cooperative Transportmentioning

confidence: 99%

Ant Colony Optimization

Dorigo¹,

Birattari²,

Stützle³

2006

IEEE Comput. Intell. Mag.

1,167

301

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“…Martinoli and Mondada [30] performed parametric simulations and real experiments for a clustering task using multiple robots. They found that the main difference is that the performance of a team of three real robots is less rapidly saturated than in simulation.…”

Section: Interferencementioning

confidence: 99%

Identification of Issues in Predicting Multi-Robot Performance through Model-Based Simulations

Dawson¹,

Wellman²,

Anderson³

2011

ICA

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Predicting the performance of intelligent multi-robot systems is advantageous because running physical experiments with teams of robots can be costly and time consuming. Controlling for every factor can be difficult in the presence of minor disparities (i.e. battery charge). Access to a variety of environmental configurations and hardware choices is prohibitive in many cases. With the eminent need for dependable robot controllers and algorithms, it is essential to understand when real robot performance can be accurately predicted. New prediction methods must account for the effects of digital and physical interaction between the robots that are more complex than just collision detection of 2D or physics-based 3D models. In this paper, we identify issues in predicting multi-robot performance and present examples of statistical and model-based simulation methods and their applicability to multi-robot systems. Even when sensor noise, latency and environmental configuration are modeled in some complexity, multi-robot systems interject interference and messaging latency, causing many prediction systems to fail to correlate to absolute or relative performance. We support this supposition by comparing results from 3D physics-based simulations to identical experiments with a physical robot team for a coverage task

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Probabilistic Modelling of a Bio-Inspired Collective Experiment with Real Robots

Cited by 14 publications

References 5 publications

Emergent Semantics Systems

Emergent Semantics Systems

Ant Colony Optimization

Identification of Issues in Predicting Multi-Robot Performance through Model-Based Simulations

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