scholarly journals Collective behavior models with vision geometrical constraints: Truncated noises and propagation of chaos

2019 ◽  
Vol 266 (9) ◽  
pp. 6109-6148
Author(s):  
Young-Pil Choi ◽  
Samir Salem
Keyword(s):  
Collective Behavior ◽  
Propagation Of Chaos ◽  
Geometrical Constraints ◽  
Behavior Models

Swarm Robotic Systems Based on Collective Behavior of Chloroplasts

2017 ◽  
Vol 29 (3) ◽  
pp. 602-612 ◽  
Author(s):  
Satoshi Hoshino ◽  
◽  
Ryo Takisawa ◽  
Yutaka Kodama ◽  
Keyword(s):  
Light Source ◽  
Collective Behavior ◽  
Autonomous Robots ◽  
Cooperative Behavior ◽  
Ground Surface ◽  
Robotic Systems ◽  
Behavioral Models ◽  
System A ◽  
Robot Behavior ◽  
Behavior Models

[abstFig src='/00290003/15.jpg' width='300' text='Swarming chloroplastic robots around light source' ] In this paper, distributed autonomous robots are used to perform area coverage tasks. In order for robots to cover the ground surface of environments, the coordination of a team of robots is a challenge. For this challenge, we present bio-inspired swarm robotic systems. We focus on the collective behavior of chloroplasts toward a light source. On the basis of the mechanism of the chloroplast, we propose robot behavior models that do not use local communication. The emergence of cooperative behavior through the interaction among the swarming robots is a main contribution of this paper. Based on simulation results, the effectiveness of the chloroplastic robots for the coverage task is discussed in terms of flexibility and scalability. Furthermore, the behavioral models are applied to actual mobile robots. Based on the results of experiments, the applicability of the chloroplastic robots to real environments is discussed. As an application of the swarm robotic system, a specific task, sweeping, is given to actual chloroplastic robots.

scholarly journals Mean-field limit for collective behavior models with sharp sensitivity regions

2018 ◽  
Vol 21 (1) ◽  
pp. 121-161 ◽  
Author(s):  
José Carrillo ◽  
Young-Pil Choi ◽  
Maxime Hauray ◽  
Samir Salem
Keyword(s):  
Collective Behavior ◽  
Mean Field ◽  
Field Limit ◽  
Mean Field Limit ◽  
Behavior Models

Plastic Deformation in Microtomed Sections

1971 ◽  
Vol 29 ◽  
pp. 458-459
Author(s):  
J. Temple Black
Keyword(s):  
Plastic Deformation ◽  
Plastic Strain ◽  
Applied Stress ◽  
Elastic Strain ◽  
High Strain ◽  
Tool Material ◽  
Cutting Edge ◽  
Material Structure ◽  
Geometrical Constraints

The output of the ultramicrotomy process with its high strain levels is dependent upon the input, ie., the nature of the material being machined. Apart from the geometrical constraints offered by the rake and clearance faces of the tool, each material is free to deform in whatever manner necessary to satisfy its material structure and interatomic constraints. Noncrystalline materials appear to survive the process undamaged when observed in the TEM. As has been demonstrated however microtomed plastics do in fact suffer damage to the top and bottom surfaces of the section regardless of the sharpness of the cutting edge or the tool material. The energy required to seperate the section from the block is not easily propogated through the section because the material is amorphous in nature and has no preferred crystalline planes upon which defects can move large distances to relieve the applied stress. Thus, the cutting stresses are supported elastically in the internal or bulk and plastically in the surfaces. The elastic strain can be recovered while the plastic strain is not reversible and will remain in the section after cutting is complete.

Voronoi Analysis of a Soccer Game

2004 ◽  
Vol 9 (3) ◽  
pp. 233-240 ◽  
Author(s):  
S. Kim
Keyword(s):  
Collective Behavior ◽  
Quantitative Assessment ◽  
The Other ◽  
Analysis Method ◽  
Random System ◽  
Soccer Game ◽  
Voronoi Polygons ◽  
The Mean

This paper describes a Voronoi analysis method to analyze a soccer game. It is important for us to know the quantitative assessment of contribution done by a player or a team in the game as an individual or collective behavior. The mean numbers of vertices are reported to be 5–6, which is a little less than those of a perfect random system. Voronoi polygons areas can be used in evaluating the dominance of a team over the other. By introducing an excess Voronoi area, we can draw some fruitful results to appraise a player or a team rather quantitatively.

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