Special Issue Editorial: Emergent Collective Behavior: From Fish Schools to Bacterial Colonies

Swarm robotics is the study of how to coordinate large groups of relatively simple robots through the use of local rules so that a desired collective behavior emerges from their interaction [...]

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Pose Estimation of Swimming Fish Using NACA Airfoil Model for Collective Behavior Analysis

Journal of Robotics and Mechatronics ◽

10.20965/jrm.2021.p0547 ◽

2021 ◽

Vol 33 (3) ◽

pp. 547-555

Author(s):

Hitoshi Habe ◽

Yoshiki Takeuchi ◽

Kei Terayama ◽

Masa-aki Sakagami ◽

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Keyword(s):

Behavior Analysis ◽

Pose Estimation ◽

Collective Behavior ◽

Estimation Method ◽

The State ◽

Video Data ◽

Body Parts ◽

Fish Schools ◽

Dynamic Variations ◽

Rapid Changes

We propose a pose estimation method using a National Advisory Committee for Aeronautics (NACA) airfoil model for fish schools. This method allows one to understand the state in which fish are swimming based on their posture and dynamic variations. Moreover, their collective behavior can be understood based on their posture changes. Therefore, fish pose is a crucial indicator for collective behavior analysis. We use the NACA model to represent the fish posture; this enables more accurate tracking and movement prediction owing to the capability of the model in describing posture dynamics. To fit the model to video data, we first adopt the DeepLabCut toolbox to detect body parts (i.e., head, center, and tail fin) in an image sequence. Subsequently, we apply a particle filter to fit a set of parameters from the NACA model. The results from DeepLabCut, i.e., three points on a fish body, are used to adjust the components of the state vector. This enables more reliable estimation results to be obtained when the speed and direction of the fish change abruptly. Experimental results using both simulation data and real video data demonstrate that the proposed method provides good results, including when rapid changes occur in the swimming direction.

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Collective Motion in Human Crowds

Current Directions in Psychological Science ◽

10.1177/0963721417746743 ◽

2018 ◽

Vol 27 (4) ◽

pp. 232-240 ◽

Cited By ~ 24

Author(s):

William H. Warren

Keyword(s):

Collective Behavior ◽

Collective Motion ◽

Local Level ◽

Self Organization ◽

Coherent Motion ◽

Global Level ◽

Crowd Behavior ◽

Local Interactions ◽

Fish Schools ◽

Emergency Situations

The balletic motion of bird flocks, fish schools, and human crowds is believed to emerge from local interactions between individuals in a process of self-organization. The key to explaining such collective behavior thus lies in understanding these local interactions. After decades of theoretical modeling, experiments using virtual crowds and analysis of real crowd data are enabling us to decipher the “rules of engagement” governing these interactions. On the basis of such results, my students and I built a dynamical model of how a pedestrian aligns his or her motion with that of a neighbor and how these binary interactions are combined within a neighborhood of interaction. Computer simulations of the model generate coherent motion at the global level and reproduce individual trajectories at the local level. This approach has yielded the first experiment-driven, bottom-up model of collective motion, providing a basis for understanding more complex patterns of crowd behavior in both everyday and emergency situations.

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Comparing the Effects of Intrinsic and Extrinsic Noise on the Vicsek Model in Three Dimensions

Volume 2: Mechatronics; Estimation and Identification; Uncertain Systems and Robustness; Path Planning and Motion Control; Tracking Control Systems; Multi-Agent and Networked Systems; Manufacturing; Intelligent Transportation and Vehicles; Sensors and Actuators; Diagnostics and Detection; Unmanned, Ground and Surface Robotics; Motion and Vibration Control Applications ◽

10.1115/dscc2017-5303 ◽

2017 ◽

Author(s):

Masoud Jahromi Shirazi ◽

Nicole Abaid

Keyword(s):

Collective Behavior ◽

Intrinsic Noise ◽

Three Dimensions ◽

Extrinsic Noise ◽

Vicsek Model ◽

Fish Schools ◽

Natural Systems ◽

Order And Disorder ◽

Noise Models ◽

Intrinsic And Extrinsic Noise

A group of simple individuals may show ordered, complex behavior through local interactions. This phenomenon is called collective behavior, which has been observed in a vast variety of natural systems such as fish schools or bird flocks. The Vicsek model is a well-established mathematical model to study collective behavior through interaction of individuals with their neighbors in the presence of noise. How noise is modeled can impact the collective behavior of the group. Extrinsic noise captures uncertainty imposed on individuals, such as noise in measurements, while intrinsic noise models uncertainty inherent to individuals, akin to free will. In this paper, the effects of intrinsic and extrinsic noise on characteristics of the transition between order and disorder in the Vicsek model in three dimensions are studied through numerical simulation.

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Research and Study of the Hybrid Algorithms Based on the Collective Behavior of Fish Schools and Classical Optimization Methods

Algorithms ◽

10.3390/a13040085 ◽

2020 ◽

Vol 13 (4) ◽

pp. 85 ◽

Cited By ~ 2

Author(s):

Liliya A. Demidova ◽

Artyom V. Gorchakov

Keyword(s):

Collective Behavior ◽

Hybrid Algorithm ◽

Gradient Descent ◽

Optimization Problems ◽

Computation Time ◽

Optimization Methods ◽

Hybrid Algorithms ◽

Fish Schools ◽

Fish School ◽

Classical Optimization

Inspired by biological systems, swarm intelligence algorithms are widely used to solve multimodal optimization problems. In this study, we consider the hybridization problem of an algorithm based on the collective behavior of fish schools. The algorithm is computationally inexpensive compared to other population-based algorithms. Accuracy of fish school search increases with the increase of predefined iteration count, but this also affects computation time required to find a suboptimal solution. We propose two hybrid approaches, intending to improve the evolutionary-inspired algorithm accuracy by using classical optimization methods, such as gradient descent and Newton’s optimization method. The study shows the effectiveness of the proposed hybrid algorithms, and the strong advantage of the hybrid algorithm based on fish school search and gradient descent. We provide a solution for the linearly inseparable exclusive disjunction problem using the developed algorithm and a perceptron with one hidden layer. To demonstrate the effectiveness of the algorithms, we visualize high dimensional loss surfaces near global extreme points. In addition, we apply the distributed version of the most effective hybrid algorithm to the hyperparameter optimization problem of a neural network.

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Ontogeny of collective behavior reveals a simple attraction rule

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1616926114 ◽

2017 ◽

Vol 114 (9) ◽

pp. 2295-2300 ◽

Cited By ~ 49

Author(s):

Robert C. Hinz ◽

Gonzalo G. de Polavieja

Keyword(s):

Animal Behavior ◽

Danio Rerio ◽

Collective Behavior ◽

Centralized Control ◽

Potential Significance ◽

Fish Schools ◽

Animal Development ◽

Collective Animal Behavior ◽

Moving Groups ◽

Attraction Behavior

The striking patterns of collective animal behavior, including ant trails, bird flocks, and fish schools, can result from local interactions among animals without centralized control. Several of these rules of interaction have been proposed, but it has proven difficult to discriminate which ones are implemented in nature. As a method to better discriminate among interaction rules, we propose to follow the slow birth of a rule of interaction during animal development. Specifically, we followed the development of zebrafish, Danio rerio, and found that larvae turn toward each other from 7 days postfertilization and increase the intensity of interactions until 3 weeks. This developmental dataset allows testing the parameter-free predictions of a simple rule in which animals attract each other part of the time, with attraction defined as turning toward another animal chosen at random. This rule makes each individual likely move to a high density of conspecifics, and moving groups naturally emerge. Development of attraction strength corresponds to an increase in the time spent in attraction behavior. Adults were found to follow the same attraction rule, suggesting a potential significance for adults of other species.

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