Geometric Guides for Interactive Evolutionary Design By Theodora Retzepi A Doctoral Thesis submitted in partial fulfilment of the requirements for the award of Doctor of Philosophy of Loughborough University August 2018 Loughborough University Wolfson School of Mechanical, Electrical and Manufacturing Engineering © Theodora Retzepi 2018 Abstract This thesis describes the addition of novel ‘Geometric Guides’ to a generative Computer- Aided Design (CAD) application that supports early-stage concept generation. The application generates and evolves abstract 3D shapes, used to inspire the form of new product concepts. It was previously a conventional Interactive Evolutionary system where users selected shapes from evolving populations. However, design industry users wanted more control over the shapes, for example by allowing the system to influence the proportions of evolving forms. The solution researched, developed, integrated and tested is a more cooperative human-machine system combining classic user interaction with innovative geometric analysis. In the literature review, different types of Interactive Evolutionary Computation (IEC), Pose Normalisation (PN), Shape Comparison, and Minimum-Volume Bounding Box approaches are compared, with some of these technologies identified as applicable for this research. Using its Application Programming Interface, add-ins for the Siemens NX CAD system have been developed and integrated with an existing Interactive Evolutionary CAD system. These add-ins allow users to create a Geometric Guide (GG) at the start of a shape exploration session. Before evolving shapes can be compared with the GG, they must be aligned and scaled (known as Pose Normalisation in the literature). Computationally-efficient PN has been achieved using geometric functions such as Bounding Box for translation and scaling, and Principle Axes for the orientation. A shape comparison algorithm has been developed that is based on the principle of non-intersecting volumes. This algorithm is also implemented with standard, readily available geometric functions, is conceptually simple, accessible to other researchers and also offers appropriate efficacy. Objective geometric testing showed that the PN and Shape Comparison methods developed are suitable for this guiding application and can be efficiently adapted to enhance an Interactive Evolutionary Design system. System performance with different population sizes was examined to indicate how best to use the new guiding capabilities to assist users in evolutionary shape searching. This was backed up by participant testing research into two user interaction strategies. A Large Background Population (LBP) approach where the GG is used to select a sub-set of shapes to show to the user was shown to be the most effective. The inclusion of Geometric Guides has taken the research from the existing aesthetic focused tool to a system capable of application to a wider range of engineering design problems. This system supports earlier design processes and ideation in conceptual design and allows a designer to experiment with ideas freely to interactively explore populations of evolving solutions. The design approach has been further improved, and expanded beyond the previous quite limited scope of form exploration. i Certificate of Originality ii iii Acknowledgements This thesis is dedicated to Laura and our son Theodore…! I would like to thank the people who have helped me through this intensive period, whose support over these three years has been an integral part of my journey. Firstly, I would like to thank Laura for her love and patience. You have always been there for me, willing to help and motivate me to become better. This work would not have been that good without your unending support and inspiration. I was amazed by your willingness to proof read my thesis, and by your patience with all of the ups and downs of my research. Sharing my life with you has made me become a more responsible person, I really feel my work has benefitted from all of this. I am especially grateful to my supervisor, Dr Ian Graham, for his advice, responsiveness and his superb guidance in the successful completion of my thesis. I feel our excellent cooperation and teamwork enabled me to exponentially grow and develop my coding ability. In addition, I would like to thank my co-Supervisor, Dr Mey Goh, for her invaluable feedback, guidance, challenging questions and insightful comments – all of which contributed to the development of my thesis and my personal growth. I would also like to thank my parents and my brother, whose unconditional love and guidance have been a constant – throughout my life, in whatever venture I pursue. Your emotional and financial support enabled me to follow my dreams to move to England and seize the opportunity of a PhD scholarship. Finally, I would like to thank the EPSRC for providing the funding which allowed me to undertake this research and for giving me the opportunity to attend conferences. This has truly been a life changing experience. iv Contents Abstract ...............................................................................i Certificate of Originality ...................................................... ii Acknowledgements ............................................................ iv Contents.............................................................................. v List of Figures ..................................................................... ix List of Tables .................................................................... xxi List of Abbreviations ...................................................... xxiii List of Nomenclature ....................................................... xxv 1 Introduction ............................................................. 1 1.1 Computer-Aided Design ....................................................................................... 1 1.2 The need for Interactive Evolutionary CAD ......................................................... 3 1.3 Wider research vision .......................................................................................... 4 1.4 Aims and Objectives ............................................................................................. 4 1.5 Novelty ................................................................................................................. 5 1.6 Contribution to Knowledge .................................................................................. 6 1.7 Thesis Structure ................................................................................................... 6 2 Literature Review .................................................... 8 2.1 Overview of generative CAD systems .................................................................. 8 2.2 Evolutionary Optimisation ................................................................................... 9 2.2.1 Evolutionary Algorithms ............................................................................. 10 2.2.2 Hybrid Simulated Annealing and Genetic Algorithm .................................. 15 2.2.3 Evolutionary Dynamic Optimisation ........................................................... 17 2.3 Interactive Evolutionary Optimisation ............................................................... 18 v 2.3.1 Pareto-optimal points Interaction Strategies ............................................. 21 2.3.2 Efficient Interaction Strategies ................................................................... 24 2.4 Interactive Evolutionary Design (IED) ................................................................ 26 2.4.1 ICE-GCAD..................................................................................................... 27 2.4.2 IDSET ........................................................................................................... 27 2.4.3 Machine Learning in IED ............................................................................. 29 2.4.3.1 Aesthetic descriptors in IED ................................................................... 31 2.4.3.2 Human preference in evolutionary art .................................................. 33 2.4.4 EvoShape..................................................................................................... 34 2.5 Geometry Mathematics ..................................................................................... 39 2.6 Pose Normalisation ............................................................................................ 42 2.6.1 Reflective Symmetry ................................................................................... 43 2.6.2 Pairwise Alignments ................................................................................... 46 2.6.3 Pose Normalisation for non-rigid shapes ................................................... 47 2.6.4 Principal Component Analysis Methods ..................................................... 49 2.6.5 Combined Pose Estimation (CPE) ................................................................ 51 2.6.6 Minimum Projection Area (MPA)................................................................ 53 2.6.7 Planar-Reflective Symmetry Transform ...................................................... 54 2.6.8 Partial Symmetry-Based Alignment ............................................................ 56 2.6.9 The Spherical Trace Transform ................................................................... 58 2.7 Minimum-Volume