An Introduction to Swarm Robotics

Navarro, Iñaki; Matı́a, Fernando

doi:10.5402/2013/608164

Cited by 162 publications

(72 citation statements)

References 52 publications

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“…Swarm robotics create collective entities using smaller single entities (Navarro and Matía, 2013). The single entities present among swarms are called agents.…”

Section: Swarm Roboticsmentioning

confidence: 99%

Swarm Robotics as a Solution to Crops Inspection for Precision Agriculture

Carbone

Garibaldi

Kurt

2018

KEG

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This paper summarizes the concept of swarm robotics and its applicability to crop inspections. To increase the agricultural yield it is essential to monitor the crop health.Hence, precision agriculture is becoming a common practice for farmers providing a system that can inspect the state of the plants ( Khosla and others, 2010). One of the rising technologies used for agricultural inspections is the use of unmaned air vehicles (UAVs) which are used to take aerial pictures of the farms so that the images could be processed to extract data about the state of the crops (Das et al., 2015). For this process both fixed wings and quadrotors UAVs are used with a preference over the quadrotor since it's easier to operate and has a milder learning curve compared to fixed wings (Kolodny, 2017). UAVs require battery replacement especially when the environmental conditions result in longer inspection times ("Agriculture -Maximize Yields with Aerial Imaging," n.d., "Matrice 100 -DJI Wiki," n.d.). As a result, inspection systems for crops using commercial quadrotors are limited by the quadrotor´s maximum flight speed, maximum flight height, quadrotor´s battery time, crops area, wind conditions, etc.("Mission Estimates," n.d.).

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“…Swarm robotics create collective entities using smaller single entities (Navarro and Matía, 2013). The single entities present among swarms are called agents.…”

Section: Swarm Roboticsmentioning

confidence: 99%

Swarm Robotics as a Solution to Crops Inspection for Precision Agriculture

Carbone

Garibaldi

Kurt

2018

KEG

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“…Here we provide a broad overview of different facets of swarm autonomy, and look especially at previous research directed at distributed swarm formation control. This section is by no means an exhaustive review of swarm robotics, but the interested reader is directed to [11], [12], [13], [14] and [15] for good reviews of the recent state of the art in this research area.…”

Section: Swarm Robotics and Swarm Intelligencementioning

confidence: 99%

“…We do not provide an overview of differences in architecture or review approaches for applications other than formation control. As before, the interested reader is directed to [11], [12], [13], and [14] if they desire greater insight into these topics.…”

Section: Swarm Robotics and Swarm Intelligencementioning

confidence: 99%

Distributed autonomy and formation control of a drifting swarm of autonomous underwater vehicles

Rypkema¹

2015

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Recent advances in autonomous underwater vehicle (AUV) technology have led to their widespread acceptance and adoption for use in scientific, commercial, and defence applications in the underwater domain. At the same time, research progress in swarm robotics has seen swarm intelligence algorithms in use with greater effect on real-world robots in the field. A group of AUVs utilizing swarm intelligence concepts has the potential to address issues more effectively than a single AUV, and such a group can potentially open up new areas of application. Examples include the monitoring and tracking of highly dynamic oceanographic phenomena such as phytoplankton blooms and the use of an AUV swarm as a virtual acoustic receiver for sea-bottom seismic surveying or the monitoring of naturally occurring acoustic radiation from cracking ice. However, the limitations of the undersea environment places unique constraints on the use of existing swarm robotics approaches with AUVs. In particular, algorithms must be distributed and robust in the face of localization error and degraded communications.This work presents an investigation into one particular swarm strategy for a group of AUVs, termed formation control, with consideration to the constraints of the underwater domain. Four formation control algorithms, each developed and tested within the MOOS-IvP framework, are presented. In addition, a 'formation quality' metric is introduced. This metric is used in conjunction with a measure of formation energy expenditure to compare the efficacy of each behaviour during construction of a desired formation, and formation maintenance while it drifts in ocean currents. This metric is also used to compare robustness of each algorithm in the presence of vehicle failure and changing communication rate.

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“…Among all the methods proposed to address the task allocation problem, this paper focuses on swarm methods, which are inspired by insect colonies where an intelligent behavior emerges from the interaction of very simple skills running on each agent (see [4,5]). Concretely, this work focuses on the so-called Response Threshold Method (RTM).…”

Section: Introductionmentioning

confidence: 99%

Indistinguishability Operators Applied to Task Allocation Problems in Multi-Agent Systems

et al. 2017

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Featured Application: Indistinguishability can provide a new family of response functions that could be applied to implement a new generation of swarm-like methods to carry out missions, like for example, allocate tasks to a set of robots in different environments. Actually, this paper provides a first implementation of this kind of systems.Abstract: In this paper we show an application of indistinguishability operators to model response functions. Such functions are used in the mathematical modeling of the task allocation problem in multi-agent systems when the stimulus, perceived by the agent, to perform a task is assessed by means of the response threshold model. In particular, we propose this kind of operators to represent a response function when the stimulus only depends on the distance between the agent and a determined task, since we prove that two celebrated response functions used in the literature can be reproduced by appropriate indistinguishability operators when the stimulus only depends on the distance to each task that must be carried out. Despite the fact there is currently no systematic method to generate response functions, this paper provides, for the first time, a theoretical foundation to generate them and study their properties. To validate the theoretical results, the aforementioned indistinguishability operators have been used to simulate, with MATLAB, the allocation of a set of tasks in a multi-robot system with fuzzy Markov chains.

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An Introduction to Swarm Robotics

Cited by 162 publications

References 52 publications

Swarm Robotics as a Solution to Crops Inspection for Precision Agriculture

Swarm Robotics as a Solution to Crops Inspection for Precision Agriculture

Distributed autonomy and formation control of a drifting swarm of autonomous underwater vehicles

Indistinguishability Operators Applied to Task Allocation Problems in Multi-Agent Systems

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