Thesis Abstract

Abstract
The field of bioinspired robotics has experienced significant growth in recent years due to its potential to create robots with enhanced capabilities by mimicking biological systems. However, developing bioinspired robotic systems often requires a complex combination of engineering, biology, and computer science expertise. To facilitate the design, development, and testing of bioinspired robotic systems, a simulation toolbox has been developed. This toolbox provides a comprehensive set of tools and resources to enable researchers and developers to simulate and evaluate bioinspired robotic systems effectively. The simulation toolbox includes modules for modeling the biomechanics of biological systems, such as muscles, tendons, and joints, as well as modules for simulating neural control algorithms inspired by biological neural networks. These modules can be easily customized and integrated to create complex bioinspired robotic systems with realistic behavior. The toolbox also includes a physics engine that accurately simulates the interactions between the robot and its environment, allowing researchers to evaluate the performance of their designs under various conditions. One of the key features of the simulation toolbox is its user-friendly interface, which allows users to quickly set up simulations, visualize results, and analyze data. The toolbox also includes a library of predefined models and controllers that users can easily modify and adapt to their specific needs. Additionally, the toolbox supports integration with popular robotics frameworks, such as ROS, enabling researchers to seamlessly transition from simulation to real-world implementation. To validate the effectiveness of the simulation toolbox, a series of case studies were conducted using different bioinspired robotic systems. These case studies demonstrated that the toolbox is capable of accurately simulating the behavior of bioinspired robotic systems and can provide valuable insights into their design and performance. Furthermore, the simulation toolbox was found to significantly reduce the time and resources required to develop and test bioinspired robotic systems, making it a valuable tool for researchers and developers in the field. In conclusion, the simulation toolbox presented in this project represents a valuable resource for the design, development, and evaluation of bioinspired robotic systems. By providing a comprehensive set of tools and resources in an easy-to-use interface, the toolbox enables researchers and developers to explore the potential of bioinspired robotics and accelerate the advancement of this exciting field.

Thesis Overview

A Simulation Toolbox for Bioinspired Robotics

SUMMARY
There is a multitude of software available for mathematical simulation, however there is no tool aimed specifically at roboticists. This project provides such a tool, designed around the terminology and research methodologies used by those interested in using biologically inspired models of neural networks to create a richer breed of robots. The simulation environment created offers tools for visualising, manipulating and recording experiments in real time, offering insight into modelling possibilities which may be suitable for robot based control systems.
Also presented is some research, using the simulator created, aimed at suggesting some new possibilities for cause of a phenomenon found in many real neural cells. Neural cells are often found to control the activity of other neural cells, and the mechanisms which permit that control are investigated.
The results show that previous conclusions about the behaviour of neurons in such scenarios may have been restricted to only a subset of cases. They also demonstrate the difficulty facing roboticists who wish to use complex models to control artificial hardware.

TABLE OF CONTENTS
1. INTRODUCTION __________________________________________________________ 1
1.1. Motivation ______________________________________________________________ 2
1.2. Report Structure __________________________________________________________ 2
2. BACKGROUND_____________________________________________________________ 3
2.1. Autonomous Robotics _____________________________________________________ 3
2.2. First Efforts _____________________________________________________________ 3
2.3. ‘Engineered’ Robotic Learning Methods ________________________________________ 4
2.4. The Influence of Cognitive Neuroscience_______________________________________ 5
2.5. Bioinspired Neural Paradigms________________________________________________ 7
2.6. Using Neuron Models in Biological Research ___________________________________ 12
2.7. The Nature of Robotic Investigations_________________________________________ 14
2.8. Tools Assisting Theoretical Robotics _________________________________________ 17
3. METHODOLOGY _________________________________________________________ 20
3.1. Requirements ___________________________________________________________ 20
3.2. Program Structure________________________________________________________ 22
3.3. Design Detail ___________________________________________________________ 24
4. IMPLEMENTATION_______________________________________________________ 32
4.1. Interactive Simulation_____________________________________________________ 32
4.2. Batch Mode ____________________________________________________________ 37
5. TESTING _________________________________________________________________ 39
5.1. Code Validation _________________________________________________________ 39
5.2. Research carried out using the simulator_______________________________________ 40
5.3. Conclusions of the Entrainment Study ________________________________________ 45
6. EVALUATION_____________________________________________________________ 47
6.1. Potential Future Work ____________________________________________________ 49
7. REFERENCES ____________________________________________________________ 51
Appendix A REFLECTION____________________________________________________ 53
Appendix B PROJECT SCHEDULE_____________________________________________ 55
B.1. Diary Extract ___________________________________________________________ 56
IV
Appendix C TEST OUTPUT ___________________________________________________ 58
Appendix D EXAMPLE SIMULATION SCREENSHOT____________________________ 61
Appendix E SCRIPTING LANGUAGE STRUCTURE______________________________

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