Self-organized adaptation of a simple neural circuit enables complex robot behaviour

@article{Steingrube2011SelforganizedAO,
  title={Self-organized adaptation of a simple neural circuit enables complex robot behaviour},
  author={Silke Steingrube and Marc Timme and Florentin W{\"o}rg{\"o}tter and Poramate Manoonpong},
  journal={ArXiv},
  year={2011},
  volume={abs/1105.1386}
}
1 Bernstein Center for Computational Neuroscience, 37073 Göttingen, Germany 2 Department of Solar Energy, Institute for Solid State Physics, ISFH / University of Hannover, 30167 Hannover, Germany 3 Network Dynamics Group, Max Planck Institute for Dynamics & Self-Organization, 37073 Göttingen, Germany 4Faculty of Physics,University of Göttingen, 37077 Göttingen, Germany Emails: silke@bccn-goettingen.de, timme@chaos.gwdg.de, worgott@bccn-goettingen.de, poramate@bccn-goettingen.de 
Novel plasticity rule can explain the development of sensorimotor intelligence
  • R. Der, G. Martius
  • Computer Science, Biology
  • Proceedings of the National Academy of Sciences
  • 2015
TLDR
This paper proposes differential extrinsic plasticity (DEP) as a new synaptic rule for self-learning systems and applies it to a number of complex robotic systems as a test case, showing seemingly purposeful and adaptive rhythmic behavior. Expand
Closed-loop Robots Driven by Short-Term Synaptic Plasticity: Emergent Explorative vs. Limit-Cycle Locomotion
TLDR
The hypothesis, that short-term synaptic plasticity (STSP) may generate self-organized motor patterns, and a wide palette of motion patterns are generated through the interaction of STSP, robot, and environment, including various forward meandering and circular motions, together with chaotic trajectories is examined. Expand
Editorial: Neural Computation in Embodied Closed-Loop Systems for the Generation of Complex Behavior: From Biology to Technology
TLDR
This eBook collects 17 cutting edge research articles, covering neural and morphological computations as well as the transfer of results to real world applications, like prosthesis and orthosis control and neuromorphic hardware implementation. Expand
General Principles of Neurorobotic Models Employing Entrainment and Chaos Control
  • Kole Harvey
  • Computer Science, Medicine
  • Front. Neurorobot.
  • 2019
TLDR
This review took at several studies of neurorobotics and generalize common principles of how they achieve this massive feat of coordinating vast numbers of sensory and motor components, relying on the key concepts of entrainment and chaos control. Expand
Incremental Embodied Chaotic Exploration of Self-Organized Motor Behaviors with Proprioceptor Adaptation
TLDR
A general and fully dynamic embodied neural system, which incrementally explores and learns motor behaviours through an integrated combination of chaotic search and reflex learning, which points out strong parallels with evolutionary search. Expand
The Playful Machine - Theoretical Foundation and Practical Realization of Self-Organizing Robots
TLDR
This paper presents a general approach to Self-Organization - Homeokinesis in a New Representation* and some examples of how this approach to self-organization in Nature and Machines has changed over time. Expand
Adaptive functional systems: learning with chaos.
TLDR
A new model of adaptive behavior that combines a winnerless competition principle and chaos to learn new functional systems that was tested in single and multigoal environments and had demonstrated a good potential for generation of new adaptations. Expand
Decentralized control of insect walking: A simple neural network explains a wide range of behavioral and neurophysiological results
TLDR
This work introduces a sensor based controller operating on artificial neurons, being applied to a (simulated) insectoid robot required to exploit the “loop through the world” allowing for simplification of neural computation and shows that such a decentralized solution leads to adaptive behavior when facing uncertain environments. Expand
Neuromorphic Closed-Loop Control of a Flexible Modular Robot by a Simulated Spiking Central Pattern Generator
TLDR
This work proposes a minimal yet highly biomimetic hierarchical controller based on a neuromorphic spiking central pattern generator (CPG) consisting of twelve simulated neurons modulated by sensory feedback that enables a modular style of controller design. Expand
Synaptic plasticity in a recurrent neural network for versatile and adaptive behaviors of a walking robot
TLDR
A bio-inspired approach to solve the task of generating versatile and adaptive behaviors for a many degrees-of-freedom (DOFs) walking robot that combines neural mechanisms with plasticity, exteroceptive sensory feedback, and biomechanics. Expand
...
1
2
3
4
5
...

References

SHOWING 1-10 OF 58 REFERENCES
An adaptive, self-organizing dynamical system for hierarchical control of bio-inspired locomotion
In this paper, dynamical systems made up of locally coupled nonlinear units are used to control the locomotion of bio-inspired robots and, in particular, a simulation of an insect-like hexapod robot.Expand
Biological Pattern Generation: The Cellular and Computational Logic of Networks in Motion
TLDR
The mode of operation of these pattern generator networks is discussed and the neural mechanisms through which they are selected and activated are considered, and the utility of computational models in analysis of the dynamic actions of these motor networks are outlined. Expand
Exploration of Natural Dynamics through Resonance and Chaos
TLDR
A dynamical exploration strategy which combines chaotic neural activity with feedback-induced resonance is introduced and can autonomously discover and tune into the intrinsic resonant modes most relevant to its body morphology. Expand
Self-Organization, Embodiment, and Biologically Inspired Robotics
Robotics researchers increasingly agree that ideas from biology and self-organization can strongly benefit the design of autonomous robots. Biological organisms have evolved to perform and survive inExpand
Complex dynamics and the structure of small neural networks
TLDR
Conditions on the connectivity structure are suggested, which guarantee the existence of complex dynamics for a considered equivalence class of network configurations, including parametrized dynamical systems with identical dynamical capacities. Expand
Sensor-driven neural control for omnidirectional locomotion and versatile reactive behaviors of walking machines
This article describes modular neural control structures for different walking machines utilizing discrete-time neurodynamics. A simple neural oscillator network serves as a central pattern generatorExpand
Modular Reactive Neurocontrol for Biologically Inspired Walking Machines
TLDR
A neurocontroller is described which generates the basic locomotion and controls the sensor-driven behavior of a four-legged and a six-legged walking machine and can easily be adapted to different types of even-leggedwalking machines without changing the internal structure and its parameters. Expand
Early motor development from partially ordered neural-body dynamics: experiments with a cortico-spinal-musculo-skeletal model
TLDR
The results show the possibility that a rich variety of meaningful behavior can be discovered and acquired by the neural-body dynamics without pre-defined coordinated control circuits. Expand
Hard-wired central pattern generators for quadrupedal locomotion
TLDR
It is demonstrated that a hard-wired CPG model, made up of four coupled nonlinear oscillators, can produce multiple phase-locked oscillation patterns that correspond to three common quadrupedal gaits — the walk, trot, and bound. Expand
Neuromodulated Control of Bipedal Locomotion Using a Polymorphic CPG Circuit
TLDR
The results show that the biped robot successfully copes with environmental perturbation by dynamically changing the torque outputs applied to the joints, and the proposed approach outperforms a monolithic CPG model with sensory feedback. Expand
...
1
2
3
4
5
...