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2018 | Book

Nonlinear Circuits and Systems for Neuro-inspired Robot Control

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About this book

This book guides readers along a path that proceeds from neurobiology to nonlinear-dynamical circuits, to nonlinear neuro-controllers and to bio-inspired robots. It provides a concise exploration of the essence of neural processing in simple animal brains and its adaptation and extrapolation to modeling, implementation, and realization of the analogous emergent features in artificial but bio-inspired robots: an emerging research field.

The book starts with a short presentation of the main areas of the Drosophila brain. These are modeled as nonlinear dynamical structures, which are then used to showcase key features like locomotion, motor learning, memory formation, and exploitation. It also discusses additional complex behaviors, such as sequence learning and perception, which have recently been discovered to exist in insects. Much of the material presented has been tested in biorobotics classes for the Master’s degree in Automation Engineering and Control of Complex Systems at the University of Catania.

Reporting on the work fostered by several national and international research projects, the book offers researchers novel ideas on how neuro-inspired dynamics can be used in developing the autonomous machines of the future.

Table of Contents

Frontmatter
Chapter 1. Biological Investigation of Neural Circuits in the Insect Brain
Abstract
Watching insects thoughtfully one cannot but adore their behavioural capabilities. They have developed amazing reproductive, foraging and orientation strategies and at the same time they followed the evolutionary path of miniaturization and sparseness. Both features together turn them into a role model for autonomous robots. Despite their tiny brains, fruit flies (Drosophila) can orient, walk on uneven terrain, in any orientation to gravity, can fly in adverse winds, find partners, places for egg laying, food and shelter. Drosophila melanogaster is the model animal for geneticists and cutting-edge tools are being continuously developed to study the underpinnings of their behavioural capabilities. This provided novel insight into the wiring and the working of central brain structures like the mushroom bodies and the central complex. Plasticity of the nervous system underlies adaptive behaviour. Drosophila flies show various memories from a 4-s working memory for orientation to a life-long body-size memory. Here we will discuss some of the functions and brain structures underlying fitness and role-model function of insects for autonomously roving robots.
Luca Patanè, Roland Strauss, Paolo Arena
Chapter 2. Non-linear Neuro-inspired Circuits and Systems: Processing and Learning Issues
Abstract
In this chapter the main elements useful for the design and realization of the neural architectures reported in the following chapters will be presented. Considering spiking and non-spiking neurons, the models used for implementing each of them, the synaptic models, the basic learning and plasticity algorithms and the network architectures will be introduced and analysed. The key elements that led to their selection and application in the developed neuro-inspired systems will be discussed briefly.
Luca Patanè, Roland Strauss, Paolo Arena
Chapter 3. Modelling Spatial Memory
Abstract
Among the different capabilities of animals, the formation of spatial memories is crucial for their life. Living beings able to move, constantly need to orient themselves in the environment to reach a target that might be not always visible. This chapter investigates the process of spatial memory formation as an essential ingredient for orientation in open and unstructured environments. Neural centres devoted to spatial memory and path integration were deeply investigated both in rats and different insect species like ants, bees and fruit flies. In this chapter a neural-inspired model for the formation of a spatial working memory is discussed considering some key elements of the insect neural centres involved, in particular the ellipsoid body of the central complex.
Luca Patanè, Roland Strauss, Paolo Arena
Chapter 4. Controlling and Learning Motor Functions
Abstract
Effective and adaptive motor functions are important for living beings and developing computational and learning mechanisms for roving robots is a crucial aspect in biorobotics. In this chapter we report a new architecture for motor learning to be applied in insect-like walking robots. The proposed model is based on the MB structure previously introduced able to memorize time evolutions of key parameters of the neural motor controller to improve existing motor primitives. The adopted control scheme enables the structure to efficiently cope with goal-oriented behavioural motor tasks. The problem of body-size evaluation is also considered and a model for the parallax-based estimation is provided. Finally, a six-legged structure, showing a steady-state exponentially stable locomotion pattern, was employed to modulate its motor commands implementing an obstacle climbing procedure. Simulation results on a Drosophila-inspired hexapod robot are reported.
Luca Patanè, Roland Strauss, Paolo Arena
Chapter 5. Learning Spatio-Temporal Behavioural Sequences
Abstract
Living beings are able to adapt their behaviour repertoire to environmental constraints. Among the capabilities needed for such improvement, the ability to store and retrieve temporal sequences is of particular importance. This chapter focuses on the description of an architecture based on spiking neurons, able to learn and autonomously generate a sequence of generic objects or events. The neural architecture is inspired by the insect mushroom bodies already taken into account in the previous chapters as a crucial centre for multimodal sensory integration and behaviour modulation in insects. Sequence learning is only one among a variety of functionalities that coexist within the insect brain computational model. We will propose a series of implementations that can be adopted to obtain these objectives and report the simulation results obtained. We will embed these mechanisms also in roving robots thereby proposing forward-thinking experiments.
Luca Patanè, Roland Strauss, Paolo Arena
Chapter 6. Towards Neural Reusable Neuro-inspired Systems
Abstract
This chapter presents an overview of some key aspects of the neuro-inspired modelling previously discussed, under the new perspective of the neural reuse theory. Here it is envisaged that the excellent capabilities shown by insects with their small neuron number and relatively low brain complexity, as compared to vertebrates, could be justified if some key neural structures are re-used for different behavioural needs. The chapter recalls some examples, found in the literature for addressing specific topics and reformulates them in relation to the neural reuse theory.
Luca Patanè, Roland Strauss, Paolo Arena
Metadata
Title
Nonlinear Circuits and Systems for Neuro-inspired Robot Control
Authors
Dr. Luca Patanè
Roland Strauss
Prof. Paolo Arena
Copyright Year
2018
Electronic ISBN
978-3-319-73347-0
Print ISBN
978-3-319-73346-3
DOI
https://doi.org/10.1007/978-3-319-73347-0