Biologically-inspired approaches for self-organization, adaptation, and collaboration of heterogeneous autonomous systems

2011 ◽  
Author(s):  
Marc Steinberg
Keyword(s):  
Autonomous Systems ◽  
Self Organization ◽  
Biologically Inspired

scholarly journals Self-Organization, Embodiment, and Biologically Inspired Robotics

Science ◽  
2007 ◽  
Vol 318 (5853) ◽  
pp. 1088-1093 ◽  
Author(s):  
R. Pfeifer ◽  
M. Lungarella ◽  
F. Iida
Keyword(s):  
Self Organization ◽  
Biologically Inspired ◽  
Biologically Inspired Robotics

scholarly journals Group formation and cohesion of active particles with visual perception–dependent motility

Science ◽  
2019 ◽  
Vol 364 (6435) ◽  
pp. 70-74 ◽  
Author(s):  
François A. Lavergne ◽  
Hugo Wendehenne ◽  
Tobias Bäuerle ◽  
Clemens Bechinger
Keyword(s):  
Visual Perception ◽  
Feedback Loop ◽  
Group Formation ◽  
Autonomous Systems ◽  
The Self ◽  
Living Systems ◽  
Self Organization ◽  
Response Threshold ◽  
Active Particles ◽  
Motility Change

Group formation in living systems typically results from a delicate balance of repulsive, aligning, and attractive interactions. We found that a mere motility change of the individuals in response to the visual perception of their peers induces group formation and cohesion. We tested this principle in a real system of active particles whose motilities are controlled by an external feedback loop. For narrow fields of view, individuals gathered into cohesive nonpolarized groups without requiring active reorientations. For wider fields of view, cohesion could be achieved by lowering the response threshold. We expect this motility-induced cohesion mechanism to be relevant not only for the self-organization of living systems, but also for the design of robust and scalable autonomous systems.

Mathematical Model of Proportion Control and Fluctuation Characteristic in Termite Caste Differentiation

2007 ◽  
Vol 19 (4) ◽  
pp. 429-435 ◽  
Author(s):  
Yusuke Ikemoto ◽  
◽  
Kuniaki Kawabata ◽  
Toru Miura ◽  
Hajime Asama ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Network Analysis ◽  
Control Strategy ◽  
Task Allocation ◽  
Autonomous Systems ◽  
Caste Differentiation ◽  
Biological Data ◽  
Self Organization ◽  
Termite Ecology ◽  
Hierarchy Generation

Self-organization of hierarchy of system has been focused in task allocation of distributed autonomous systems and network analysis. It is important to realize the mechanism of hierarchy generation for implementation in artificial systems. In order to know the principle, we try to model the control of caste differentiations in the termite ecology. Equations of evolution are created, using both of biological data and assumptions obtained by mathematical analysis. In addition, the model is validated by computer simulations. In this study, we propose that the probability migration of individuals and modulations of fluctuation are operated as a differentiation control strategy.

scholarly journals Self-Corrective Autonomous Systems using Optimization Processes for Detection and Correction of Unexpected Error Conditions

2016 ◽  
Vol 5 (4) ◽  
pp. 262
Author(s):  
Nicoladie D. Tam
Keyword(s):  
Autonomous Systems ◽  
Corrective Feedback ◽  
Biological Evolution ◽  
Optimization Process ◽  
Feedback Systems ◽  
Biologically Inspired ◽  
External Assistance ◽  
Actual Outcome ◽  
Disparity Vector ◽  
Corrective Actions

<p>A theoretical framework for autonomous self-detection and self-correction of unexpected error conditions is derived by incorporating the principles of operation in autonomous control in biological evolution.  Using the biologically inspired principles, the time-dependent multi-dimensional disparity vector is used as a quantitative metric for detecting unexpected and unforeseeable error conditions without any external assistance.  The disparity vector is a measure of the discrepancy between the expected outcome predicted by the autonomous system and the actual outcome in the real world.  It is used as a measure to detect any unexpected or unforeseeable errors.  The process for autonomous self-correction of the self-discovered errors is an optimization process to minimize the errors represented by the disparity vectors.  The strategies for prioritizing the urgency of corrective actions are also provided in the theoretical derivations.  The criteria for any change in direction of the corrective actions are also provided quantitatively.  The criteria for the detection of the minimization and maximization of errors are also provided in the autonomous optimization process.  The biological correspondences of the emotional responses in relation to the autonomic self-corrective feedback systems are also provided.</p>

Biologically inspired, haltere, angular-rate sensors for micro-autonomous systems

2012 ◽  
Author(s):  
G. L. Smith ◽  
S. S. Bedair ◽  
B. E. Schuster ◽  
W. D. Nothwang ◽  
J. S. Pulskamp ◽  
...  
Keyword(s):  
Angular Rate ◽  
Autonomous Systems ◽  
Biologically Inspired

Autonomous Systems with Emergent Behavior

2007 ◽  
pp. 429-443 ◽  
Author(s):  
G. D.M. Serugendo
Keyword(s):  
Large Scale ◽  
Autonomous Systems ◽  
Emergent Behavior ◽  
Self Organization ◽  
Central Control ◽  
Manufacturing Control ◽  
Government Services ◽  
Potential Applications ◽  
Engineered Systems

This chapter presents the notion of autonomous engineered systems working without central control through self-organization and emergent behavior. It argues that future large-scale applications from domains as diverse as networking systems, manufacturing control, or e-government services will benefit from being based on such systems. The goal of this chapter is to highlight engineering issues related to such systems, and to discuss some potential applications.

A GOAL-ORIENTATION FRAMEWORK FOR SELF-ORGANIZING CONTROL

2013 ◽  
Vol 16 (02n03) ◽  
pp. 1350002
Author(s):  
FRANK HESSE ◽  
FLORENTIN WÖRGÖTTER
Keyword(s):  
Goal Orientation ◽  
Adaptive Learning ◽  
Autonomous Robots ◽  
Self Organization ◽  
Biologically Inspired ◽  
Motor Primitives ◽  
Biologically Inspired Robots ◽  
System A ◽  
Open Question ◽  
Adaptive Learning Systems

Self-organization, especially in the framework of embodiment in biologically inspired robots, allows the acquisition of behavioral primitives by autonomous robots themselves. However, it is an open question how self-organization of basic motor primitives and goal-orientation can be combined, which is a prerequisite for the usefulness of such systems. In the paper at hand we propose a goal-orientation framework allowing the combination of self-organization and goal-orientation for the control of autonomous robots in a mutually independent fashion. Self-organization based motor primitives are employed to achieve a given goal. This requires less initial knowledge about the properties of robot and environment and increases adaptivity of the overall system. A combination of self-organization and reward-based learning seems thus a promising route for the development of adaptive learning systems.

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