The Cooperation of Heterogeneous Mobile Robot Configurations in Advanced Manufacturing Environments Author: Supervisor: Mr. Nicol Naidoo Prof. Glen Bright Co-supervisor: Dr. Riaan Stopforth A dissertation submitted in fulfilment of the requirements for the degree of Master of Science in Engineering in the Mechatronics and Robotics Research Group School of Engineering November 2014 Declaration of Authorship I, Mr. Nicol Naidoo, declare that this dissertation titled, `The Cooperation of Het- erogeneous Mobile Robot Configurations in Advanced Manufacturing En- vironments' and the work presented in it are my own. I confirm that: The research reported in this dissertation, except where otherwise indicated, is my original research. This dissertation has not been submitted for any degree or examination at any other university. This dissertation does not contain other persons' data, pictures, graphs or other information, unless specifically acknowledged as being sourced from other persons. This dissertation does not contain other persons' writing, unless specifically ac- knowledged as being sourced from other researchers. Where other written sources have been quoted, then: (a) their words have been re-written but the general in- formation attributed to them has been referenced, or (b) where their exact words have been used, then their writing has been placed in italics and inside quotation marks, and referenced. This dissertation does not contain text, graphics or tables copied and pasted from the Internet, unless specifically acknowledged, and the source being detailed in the dissertation and in the References sections. Signed: Date: Declaration by Supervisor As the candidate's Supervisor, I agree to the submission of this dissertation. Signed: Date: i Declaration of Publications DETAILS OF CONTRIBUTION TO PUBLICATIONS that form part and/or include research presented in this dissertation (include publications in preparation, submitted, in press and published and give details of the contributions of each author to the exper- imental work and writing of each publication). Publication 1: Conference Proceedings: 6th Robotics and Mechatronics Conference (RobMech), \Material Flow Optimisation in Flexible Manufacturing Systems", 30-31 October 2013. Mr. N. Naidoo: Research, simulation, application and main author. Prof. G. Bright: Technical guidance, co-author. Dr. R. Stopforth: Technical guidance, co-author. Publication 2: Conference Proceedings: 8th International Conference on Intelligent Sys- tems and Agents, \Cooperative Autonomous Robot Agents in Flexible Manufacturing Systems", 15-17 July 2014. Mr. N. Naidoo: Research, simulation, application and main author. Prof. G. Bright: Technical guidance, co-author. Dr. R. Stopforth: Technical guidance, co-author. Publication 3: Journal Paper in Preparation: \Support Vector Machine Learning in Multi-Robot Teams". Mr. N. Naidoo: Research, simulation, application and main author. Prof. G. Bright: Technical guidance, co-author. Dr. R. Stopforth: Technical guidance, co-author. Signed: Date: ii Abstract Cooperation of Multiple Mobile Robot Systems (MMRS) have drawn increasing atten- tion in recent years since these systems have the ability to perform complex tasks more efficiently compared to Single Mobile Robot Systems (SMRS). An implementation of a cooperative MMRS in a manufacturing environment can, for example, solve the issue of bottlenecks in a production line, whereas the limitations of a SMRS can lead to a lot of problems in terms of time wastage, loss of revenue, poor quality products and dissatisfied customers. The study of cooperation in heterogeneous robot teams has evolved due to the engineer- ing and economic benefits attribute as well as the existence of diversities in homogeneous robot teams. The challenge of cooperation in these systems is a result of the task tax- onomies and fundamental abilities of each robot in the team; there is therefore a need for an Artificial Intelligence (AI) system that processes these heterogeneities to facilitate robot cooperation. This dissertation focuses on the research, design and development of an artificial intel- ligence for a team of heterogeneous mobile robots. The application of the system was directed towards advanced manufacturing systems, however, it can be adapted to search and rescue tasks. An essential component of the AI design is the machine learning algorithm which was used to predict suitable goal destinations for each mobile robot, given a set of input pa- rameters. Mobile robot autonomy was achieved through the development of an obstacle avoidance and navigation system. The AI was also interfaced to a Supervisory Control and Data Acquisition System (SCADA) which facilitates end-user interaction { a vital ingredient to manufacturing automation systems. iii Acknowledgements I would like to acknowledge and express my sincere thanks to the following people and organisations: My supervisors, Professor Glen Bright and Dr. Riaan Stopforth for their super- vision, guidance and provision of resources for the research. I thoroughly enjoyed every form of communication with them as it motivated me to do my best. To the directors, senior managers and HR staff at my company, Clifford Welding Systems, for their interest in developing my career as well as funding this degree. NAI Manufacturing for fabricating the metalwork for the robots at no cost. My family, for their unconditional love and support throughout this degree, es- pecially my wife, Aurelle, who has played a pivotal role in the work presented in this research. I truly appreciate the sacrifices she endured during this degree and I commend her for the support and encouragement during the late nights and long weekends. My Lord and Saviour, Jesus Christ, who has always been with me and helped me through every challenge I faced in this degree. All praise and honour to Him for the multiple blessings He has graced me with and for the great privilege I have in getting to know Him. iv Contents Declaration of Authorshipi Declaration of Publications ii Abstract iii Acknowledgements iv Contents v List of Figures ix List of Tables xi Abbreviations xii 1 Introduction1 1.1 Robot heterogeneity in manufacturing environments............2 1.2 Bottlenecks in manufacturing environments.................3 1.3 Productivity and supply chain management.................3 1.4 Literature Survey................................4 1.4.1 The Mechatronic system........................4 1.4.2 Perception................................5 1.4.2.1 Odometry...........................6 1.4.2.2 Range finder sensors.....................7 1.4.2.3 Inertial sensing and navigation...............8 1.4.3 Localisation and mapping.......................9 1.4.4 Cognition................................ 11 1.4.4.1 Path planning........................ 12 1.4.4.2 Obstacle avoidance..................... 12 1.4.5 Middleware in robotic networks.................... 13 1.4.6 Cooperation in mobile robot teams.................. 15 1.4.6.1 Control architectures.................... 16 1.4.6.2 Related research....................... 17 1.5 Problem statement............................... 19 1.6 Research objectives and contributions.................... 19 v Contents vi 1.7 Design specifications.............................. 20 1.8 Research publications............................. 21 1.9 Chapter summary............................... 22 2 Mechatronic Architecture Design 23 2.1 Architecture design overview......................... 23 2.2 Robot hardware................................. 25 2.2.1 Performance PeopleBot........................ 25 2.2.2 Segway RMP200............................ 26 2.2.3 Segway RMP400............................ 28 2.3 Sensor hardware................................ 29 2.3.1 Laser range finder sensors....................... 29 2.3.2 Sonar range finder sensors....................... 32 2.4 Chapter summary............................... 32 3 Mechatronic System Design 33 3.1 System design overview............................ 33 3.2 Artificial intelligence design.......................... 35 3.2.1 The Player Project middleware.................... 35 3.2.1.1 Client-server framework................... 36 3.2.1.2 Interfaces and drivers.................... 36 3.2.1.3 Stage............................. 37 3.2.1.4 File types........................... 37 3.2.2 Localisation............................... 38 3.2.3 Cognition................................ 38 3.2.4 Machine learning............................ 39 3.2.4.1 SVM background...................... 40 3.2.4.2 SVM linear classifiers.................... 40 3.2.4.3 SVM non-linear classifiers.................. 43 3.2.4.4 Multi-class SVM....................... 43 3.2.4.5 SVM software libraries................... 44 3.3 SCADA design................................. 44 3.4 Operating system kernel............................ 45 3.5 System design overview (revisited)...................... 46 3.6 Chapter summary............................... 46 4 Software Development 47 4.1 AI development overview........................... 47 4.2 Player server configuration........................... 49 4.2.1 Simulation drivers and interfaces................... 49 4.2.2 Real-world drivers and interfaces................... 50 4.3 Client applications............................... 51 4.3.1 Player proxies and methods...................... 51 4.3.2 Cognition module........................... 52 4.3.2.1 Cognition program structure................ 52 4.3.2.2 Turning in tight spaces................... 54 4.3.2.3 Local