A self-adaptive landmark-based aggregation method for robot swarms

Date

2021-01-01

Author

Sadeghi Amjadi, Arash
Raoufi, Mohsen
Turgut, Ali Emre

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

221
views

0
downloads

Aggregation, a widely observed behavior in social insects, is the gathering of individuals on any location or on a cue. The former being called the self-organized aggregation, and the latter being called the cue-based aggregation. One of the fascinating examples of cue-based aggregation is the thermotactic behavior of young honeybees. Young honeybees aggregate on optimal temperature zones in the hive using a simple set of behaviors. The state-of-the-art cue-based aggregation method BEECLUST was derived based on these behaviors. The BEECLUST method is a very simple, yet a very capable method that has favorable characteristics such as robustness to noise and simplicity to apply. However, the BEECLUST method does not perform well in low robot densities. In this article, inspired by the navigation techniques used by ants and bees, a self-adaptive landmark-based aggregation method is proposed. In this method, robots use landmarks in the environment to locate the cue once they "learn" the relative position of the cue with respect to the landmark. With the introduction of an error threshold parameter, the method also becomes adaptive to changes in the environment. Through systematic experiments in kinematic and realistic simulators with different parameters, robot densities, and cue sizes, it was observed that using the information of the environment makes the proposed method to show better performance than the BEECLUST in all the settings, including low robot density, high noise, and dynamic conditions.

URI

https://hdl.handle.net/11511/88830

Journal

ADAPTIVE BEHAVIOR

DOI

https://doi.org/10.1177/1059712320985543

Collections

Department of Mechanical Engineering, Article

Suggestions

OpenMETU
Core

Landmark-based Aggregation method for Robot Swarms Sadeghi Amjadi, Arash; Turgut, Ali Emre; Department of Mechanical Engineering (2021-8-3) Aggregation, a widely observed behavior in social insects, is the gathering of individuals at any location or on a cue. The former being called self-organized aggregation, and the latter being called cue-based aggregation. One of the fascinating examples of cue-based aggregation is the thermotactic behavior of young honeybees. Young honeybees aggregate on optimal temperature zones in the hive using a simple set of behaviors. The state-of-the-art cue-based aggregation method BEECLUST was derived based on the...
An Experimental investigation of change blindness by group eye tracking paradigm Göl, Aysel Yasemin; Acartürk, Cengiz; Department of Cognitive Sciences (2018) The group effect refers to a decline in vigilance when an individual is in a social, group setting. Due to a diluted risk of being preyed upon and a higher number of group members that can detect a predator, members are less alert when they are in a group. The present study investigates if such an effect can be observed in human participants in a simple change detection task by employing group eye tracking (GET) paradigm. For this end, the visual phenomenon of change blindness is explored. In a within-subje...
A multi-technique approach to determine temporal and spatial variability of groundwater-stream water exchange Koruk, Kasimcan; Yılmaz, Koray Kamil; Akyürek, Sevda Zuhal; Binley, Andrew (null; 2019-04-07) Characterizing the spatio-temporal distribution of groundwater-surface water exchange fluxes are of paramountimportance in understanding catchment behavior as well as biogeochemical and ecological status. The objectiveof this study is to quantify the spatio-temporal distribution of the exchange fluxes along the Cakit Stream(Nigde, Turkey) through coupling a set of geophysical techniques and in-stream measurements in a hierarchicalmanner. First, we conducted electromagnetic induction (EM) sur...
A coupled plankton-anchovy population dynamics model assessing nonlinear controls of anchovy and gelatinous biomass in the Black Sea OĞUZ, Temel; Salihoğlu, Barış; Fach Salihoğlu, Bettina Andrea (2008-01-01) A coupled model of lower trophic levels and anchovy Engraulis encrasicolus ponticus population dynamics was developed to analyze the mechanisms controlling sharp anchovy and gelatinous zooplankton biomass transitions from the 1960s to the 1980s in the Black Sea. An increase in anchovy stocks from estimated low (similar to 300 kt) to moderate (similar to 700 kt) in the late 1960s was related to weakening piscivore predation pressure, slight nutrient enrichment of the basin during an early eutrophication phas...
Strong population structure in a species manipulated by humans since the Neolithic: the European fallow deer (Dama dama dama) Baker, K. H.; Gray, H. W. I.; Ramovs, V.; Mertzanidou, D.; AKIN PEKŞEN, Çiğdem; Bilgin, Cemal Can; Sykes, N.; Hoelzel, A. R. (2017-07-01) Species that have been translocated and otherwise manipulated by humans may show patterns of population structure that reflect those interactions. At the same time, natural processes shape populations, including behavioural characteristics like dispersal potential and breeding system. In Europe, a key factor is the geography and history of climate change through the Pleistocene. During glacial maxima throughout that period, species in Europe with temperate distributions were forced south, becoming distribut...

Citation Formats

A. Sadeghi Amjadi, M. Raoufi, and A. E. Turgut, “A self-adaptive landmark-based aggregation method for robot swarms,” ADAPTIVE BEHAVIOR, pp. 0–0, 2021, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/88830.