Adaptive foraging for simulated and real robotic swarms: the dynamical response threshold approach

Castello, Eduardo; Yamamoto, Tomoko; Libera, Fabio Dalla; Liu, Wenguo; Winfield, Alan F. T.; Nakamura, Yutaka; Ishiguro, Hiroshi

doi:10.1007/s11721-015-0117-7

Cited by 81 publications

(38 citation statements)

References 39 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the prey-retrieval task studied in [29], the authors demonstrate via robotic experiments that allowing robots to modify their tendency to participate in the primary task leads to reduced interference. Similar studies predefine participatory tendencies in robots [28], or allow them to adjust it online [7], demonstrating an improvement in efficiency by running experiments.…”

Section: Related Workmentioning

confidence: 82%

“…For the following parameters: λ p = 1.32, λ d = 1.32, C = 0.03, δ = 0.1, v = 0.1, each robot computes the optimal swarm density using (7). The robots perform an unbiased random walk in the domain while encountering other robots.…”

Section: Resultsmentioning

confidence: 99%

“…In the context of multi-robot foraging [7], [8] and collection tasks [9], [10], it has been shown that while adding more robots to the swarm at intermediate robot densities increases the total number of objects collected, the increase in performance is sub-linear-caused by a significant decrease in individual robot performance, e.g., [11], [12]. Owing to the increased operational cost of deploying large robot teams, one would like to obtain the desired overall productivity while utilizing as few robots as possible [13].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Voluntary Retreat for Decentralized Interference Reduction in Robot Swarms

Mayya

Pierpaoli

Egerstedt

2019

2019 International Conference on Robotics and Automation (ICRA)

View full text Add to dashboard Cite

In densely-packed robot swarms operating in confined regions, spatial interference -which manifests itself as a competition for physical space -forces robots to spend more time navigating around each other rather than performing the primary task. This paper develops a decentralized algorithm that enables individual robots to decide whether to stay in the region and contribute to the overall mission, or vacate the region so as to reduce the negative effects that interference has on the overall efficiency of the swarm. We develop this algorithm in the context of a distributed collection task, where a team of robots collect and deposit objects from one set of locations to another in a given region. Robots do not communicate and use only binary information regarding the presence of other robots around them to make the decision to stay or retreat. We illustrate the efficacy of the algorithm with experiments on a team of real robots.

show abstract

Section: Related Workmentioning

confidence: 82%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Voluntary Retreat for Decentralized Interference Reduction in Robot Swarms

Mayya

Pierpaoli

Egerstedt

2019

2019 International Conference on Robotics and Automation (ICRA)

View full text Add to dashboard Cite

show abstract

“…For example, in a foraging scenario, one subgroup of robots could be tasked to bring resources back to the nest, another subgroup is assigned to actively scout for additional resources in an unknown environment, while a third subgroup is tasked with defending the nest. [94][95][96][97] For the dynamic task allocation experiment, herein, the Card Dealer's algorithm in ref. [65] was chosen for implementation.…”

Section: Swarm Scenario 4: Dynamic Task Allocationmentioning

confidence: 99%

Design and implementation of a millirobot for swarm studies –mROBerTO

Kim¹,

Kashino²,

Colaco³

et al. 2018

Robotica

View full text Add to dashboard Cite

SUMMARYThe use of millirobots, particularly in swarm studies, would enable researchers to verify their proposed autonomous cooperative behavior algorithms under realistic conditions with a large number of agents. While multiple designs for such robots have been proposed, they, typically, require custom-made components, which make replication and manufacturing difficult, and, mostly, employ non-modular integral designs. Furthermore, these robots' proposed small sizes tend to limit sensory perception capabilities and operational time. Some have resolved few of the above issues through the use of extensions that, unfortunately, add to their size.In contribution to the pertinent field, thus, a novel millirobot with an open-source design, addressing the above concerns, is presented in this paper. Our proposed millirobot has a modular design and uses easy to source, off-the-shelf components. Themilli-robot-Toronto (mROBerTO) also includes a variety of sensors and has a 16 × 16 mm2footprint.mROBerTO's wireless communication capabilities include ANT™, Bluetooth Smart, or both simultaneously. Data-processing is handled by an ARM processor with 256 KB of flash memory. Additionally, the sensing modules allow for extending or changing the robot's perception capabilities without adding to the robot's size. For example, the swarm-sensing module, designed to facilitate swarm studies, allows for measuring proximity and bearing to neighboring robots and performing local communications.Extensive experiments, some of which are presented herein, have illustrated the capability ofmROBerTOunits for use in implementing a variety of commonly proposed swarm algorithms.

show abstract

“…As the probability of executing a task only depends on the current task, or state, the decision process can be modeled as a probabilistic Markov chain. Some examples of methods based on Response Threshold can be found in [6][7][8][9]. This classical probabilistic approach presents some well known disadvantages (see [10]), for instance problems associated with the selection of the probability function (response function) when more than two tasks are considered, asymptotic converge to a system's stable state, and so on.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2017

View full text Add to dashboard Cite

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.

show abstract

Adaptive foraging for simulated and real robotic swarms: the dynamical response threshold approach

Cited by 81 publications

References 39 publications

Voluntary Retreat for Decentralized Interference Reduction in Robot Swarms

Voluntary Retreat for Decentralized Interference Reduction in Robot Swarms

Design and implementation of a millirobot for swarm studies –mROBerTO

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

Contact Info

Product

Resources

About