Optimization of stochastic strategies for spatially inhomogeneous robot swarms: A case study in commercial pollination

Berman,; Nagpal,; Halász,

doi:10.1109/iros.2011.6048378

Cited by 3 publications

(9 citation statements)

References 17 publications

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“…In Berman et al (2011b), this approach is applied to an area coverage task. Dantu et al (2012) compared the results obtained in this work with those obtained from a simulation of the same behavior.…”

Section: Macroscopic Modelsmentioning

confidence: 99%

Swarm robotics: a review from the swarm engineering perspective

et al. 2013

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Swarm robotics is an approach to collective robotics that takes inspiration from the self-organized behaviors of social animals. Through simple rules and local interactions, swarm robotics aims at designing robust, scalable, and flexible collective behaviors for the coordination of large numbers of robots. In this paper, we analyze the literature from the point of view of swarm engineering: we focus mainly on ideas and concepts that contribute to the advancement of swarm robotics as an engineering field and that could be relevant to tackle real-world applications. Swarm engineering is an emerging discipline that aims at defining systematic and well founded procedures for modeling, designing, realizing, verifying, validating, operating, and maintaining a swarm robotics system. We propose two taxonomies: in the first taxonomy, we classify works that deal with design and analysis methods; in the second taxonomy, we classify works according to the collective behavior studied. We conclude with a discussion of the current limits of swarm robotics as an engineering discipline and with suggestions for future research directions.

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Section: Macroscopic Modelsmentioning

confidence: 99%

Swarm robotics: a review from the swarm engineering perspective

et al. 2013

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“…2) that has substantial computing and storage resources and the ability to recharge the MAVs, which have the capabilities outlined in [4]. Each MAV is considered to have the ability to localize itself within the region of the environment that it currently occupies (see Fig.…”

Section: B Swarm Control Architecturementioning

confidence: 99%

“…We have previously presented a scalable approach to optimizing robot control policies for a target collective behavior in robotic swarms with arbitrary spatial distributions [4]. This approach, which we refer to here as OptRAD, abstracts the swarm to a macroscopic continuous model.…”

Section: A Overviewmentioning

confidence: 99%

“…We compare the utility of a deterministic task allocation approach using the resource management system Karma [7] and a stochastic approach OptRAD [4], which is based on the optimization of a spatiotemporal model of the swarm population dynamics. These two approaches were developed for swarms of highly resource-constrained robots that must adapt to disturbances and failures.…”

Section: Introductionmentioning

confidence: 99%

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confidence: 99%

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A comparison of deterministic and stochastic approaches for allocating spatially dependent tasks in micro-aerial vehicle collectives

Dantu

Berman

Kate

et al. 2012

2012 IEEE/RSJ International Conference on Intelligent Robots and Systems

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Abstract-We compare our previously developed deterministic [7] and stochastic [3], [4] strategies for allocating tasks in robotic swarms 1 consisting of very large populations of highly resource-constrained robots. We study our two task allocation approaches in a simulated scenario in which a collective of insect-inspired micro-aerial vehicles (MAVs) must produce a specified spatial distribution of pollination activity over a crop field. We investigate the approaches' requirements, advantages, and disadvantages under realistic conditions of error in robot localization, navigation, and sensing in simulation. Our results show that the deterministic approach, which requires regionbased robot navigation, yields higher task progress in all cases. For robots without such navigation capabilities, the stochastic approach is a feasible alternative, and its resulting task progress is less sensitive to error in localization, error in navigation, and a combination of high error in localization, navigation, and sensing.

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Research Progress on Synergistic Technologies of Agricultural Multi-Robots

Mao

Liu

et al. 2021

Applied Sciences

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Multi-robots have shown good application prospects in agricultural production. Studying the synergistic technologies of agricultural multi-robots can not only improve the efficiency of the overall robot system and meet the needs of precision farming but also solve the problems of decreasing effective labor supply and increasing labor costs in agriculture. Therefore, starting from the point of view of an agricultural multiple robot system architectures, this paper reviews the representative research results of five synergistic technologies of agricultural multi-robots in recent years, namely, environment perception, task allocation, path planning, formation control, and communication, and summarizes the technological progress and development characteristics of these five technologies. Finally, because of these development characteristics, it is shown that the trends and research focus for agricultural multi-robots are to optimize the existing technologies and apply them to a variety of agricultural multi-robots, such as building a hybrid architecture of multi-robot systems, SLAM (simultaneous localization and mapping), cooperation learning of robots, hybrid path planning and formation reconstruction. While synergistic technologies of agricultural multi-robots are extremely challenging in production, in combination with previous research results for real agricultural multi-robots and social development demand, we conclude that it is realistic to expect automated multi-robot systems in the future.

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Optimization of stochastic strategies for spatially inhomogeneous robot swarms: A case study in commercial pollination

Cited by 3 publications

References 17 publications

Swarm robotics: a review from the swarm engineering perspective

Swarm robotics: a review from the swarm engineering perspective

A comparison of deterministic and stochastic approaches for allocating spatially dependent tasks in micro-aerial vehicle collectives

Research Progress on Synergistic Technologies of Agricultural Multi-Robots

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