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    Low latency vision-based control for robotics : a thesis presented in partial fulfilment of the requirements for the degree of Master of Engineering in Mechatronics at Massey University, Manawatu, New Zealand
    (Massey University, 2018) Lues, Joshua
    In this work, the problem of controlling a high-speed dynamic tracking and interception system using computer vision as the measurement unit was explored. High-speed control systems alone present many challenges, and these challenges are compounded when combined with the high volume of data processing required by computer vision systems. A semi-automated foosball table was chosen as the test-bed system because it combines all the challenges associated with a vision-based control system into a single platform. While computer vision is extremely useful and can solve many problems, it can also introduce many problems such as latency, the need for lens and spatial calibration, potentially high power consumption, and high cost. The objective of this work is to explore how to implement computer vision as the measurement unit in a high-speed controller, while minimising latencies caused by the vision itself, communication interfaces, data processing/strategy, instruction execution, and actuator control. Another objective was to implement the solution in one low-latency, low power, low cost embedded system. A field programmable gate array (FPGA) system on chip (SoC), which combines programmable digital logic with a dual core ARM processor (HPS) on the same chip, was hypothesised to be capable of running the described vision-based control system. The FPGA was used to perform streamed image pre-processing, concurrent stepper motor control and provide communication channels for user input, while the HPS performed the lens distortion mapping, intercept calculation and “strategy” control tasks, as well as controlling overall function of the system. Individual vision systems were compared for latency performance. Interception performance of the semi-automated foosball table was then tested for straight, moderate-speed shots with limited view time, and latency was artificially added to the system and the interception results for the same, centre-field shot tested with a variety of different added latencies. The FPGA based system performed the best in both steady-state latency, and novel event detection latency tests. The developed stepper motor control modules performed well in terms of speed, smoothness, resource consumption, and versatility. They are capable of constant velocity, constant acceleration and variable acceleration profiles, as well as being completely parameterisable. The interception modules on the foosball table achieved a 100% interception rate, with a confidence interval of 95%, and reliability of 98.4%. As artificial latency was added to the system, the performance dropped in terms of overall number of successful intercepts. The decrease in performance was roughly linear with a 60% in reduction in performance caused by 100 ms of added latency. Performance dropped to 0% successful intercepts when 166 ms of latency was added. The implications of this work are that FPGA SoC technology may, in future, enable computer vision to be used as a general purpose, high-speed measurement system for a wide variety of control problems.
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    Function block programming for distributed control : a thesis presented in complete fulfilment of the requirements for the Master of Engineering, 216.899 thesis at Massey University, Wellington, New Zealand
    (Massey University, 2004) Meek, Andrew Robert
    This report discusses research and development using the draft IEC 61499 function block standard for distributed control with embedded microprocessor applications. This is a function block programming language that is currently under development for programming distributed control systems. The report covers what is required to develop an IEC 61499 compliant product and its suitablity for use with distributed control systems. To utilise the IEC 61499 standard, research and development of an embedded Java platform was performed. This required porting a Java virtual machine to run on an embedded microprocessor. An existing industrial network protocol DeviceNet was chosen for distributing the data between the network of control devices. To achieve this an upgrade was required to an existing DeviceNet communications engine to support distributed control. A third party IEC 61499 software application engine was ported to run on an embedded microprocessor. This option was chosen rather than completely developing a software engine as a commercial decision by the developer company. It also allowed support from other companies and researchers working with this standard. To test distributed control using this function block programming standard a test application consisting of a conveyor and three axis robot was developed. The test application demonstrated the feasibility of distributed control using IEC 61499 function blocks and some of the advantages of distributed control. Further outcomes of this research have highlighted some of the problems that require rectifying before this function block programming standard is feasible for commercial products.
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    On the use of optimal search algorithms with artificial potential field for robot soccer navigation : Computer Science, Master of Science
    (Massey University, 2018) Dong, Chen
    The artificial potential field (APF) is a popular method of choice for robot navigation, as it offers an intuitive model clearly defining all attractive and repulsive forces acting on the robot [3] [25] [29] [43] [50]. However, there are drawbacks that limit the usage of this method. For instance, the local minima problem that gets a robot trapped, and the Goal-Non-Reachable-with-Obstacle-Nearby (GNRON) problem, as reported in [51] [5] [23] [2] and [3]. In order to avoid these limitations, this research focuses on devising a methodology of combining the artificial potential field with a selection of optimal search algorithms. This work investigates the performance of the method when using different optimal search algorithms such as the A* algorithm and the any-angle path-planning Theta* Search, in combination with different types of artifcial potential field generators. We also present a novel integration technique, whereby the Potential Field approach is utilized as an internal component of an optimal search algorithm, considering the safeness of the calculated paths. Furthermore, this study also explores the optimization of several auxiliary algorithms used in conjunction with the APF-Optimal search integration: There are three different methods proposed for implementing the line-of-sight (LOS) component of the Theta* search, namely the simple line-of-sight checking algorithm, the modified Bresenham's line algorithm and the modified Cohen-Sutherland algorithm. Contrary to the studies presented in [5], [42], [48] and [40] where the APF and the optimal search algorithms were used separately, in this research, an integrative methodology involving the APF inside the optimal search with a newly proposed Safety Factor (SF) is explored. Experiment results indicate that the APF-A* Search with the SF can reduce the number of state expansions and therefore also the running time up to 19.61%, while maintaining the safeness of the path, as compared to APF-A* when not using the SF. Furthermore, this research also explores how the proposed hybrid algorithms can be used in developing multi-objective behaviours of single robot. In this regard, a robot soccer simulation platform with a physics engine is developed as well to support the exploration. Lastly, the performance of the proposed algorithms is examined under varying environment conditions. Evidences are provided showing that the method can be used in constructing the intelligence for a robot goal keeper and a robot attacker (ball shooter). A multitude of AI robot behaviours using the proposed methods are integrated via a finite state machine including: defensive positioning/parking, ball kicking/shooting, and target pursuing behaviours. Keywords : Artificial Potential Field, Optimal Searches, Robot Navigation, Multi- objective Behaviours.
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    Modelling of the drying section of a continuous paper machine : a thesis presented in partial fulfilment of the requirement for the degree of Master in Production Technology at Massey University
    (Massey University, 1996) Ma, Huiting
    The invention of paper in 105 A.D. was a milestone in the history of civilization and demand for paper has been increasing steadily ever since. Although it has become more and more popular to store, process and transfer information in electronic forms, paper is to date still the most common means for recording information. According to Storat (1993), production in the last twenty years has increased by more than 60 percent, while capital expenditures in the industry have grown to almost 12 percent of sales, or double the average expenditures of other manufacturing industries. This capital investment has gone towards capacity expansion and extensive rebuilds of existing mills - almost 60 percent of the existing capacity comes from modern facilities containing machines either newly installed or rebuilt in the past ten years. As a result, fossil fuel and energy consumption in this industry fell by 46 percent in the last two decades.[FROM INTRODUCTION]
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    Mathematical modelling and control of a robotic manipulator : a thesis presented in partial fulfilment of the requirements of the degree of Masters of Technology at Massey University
    (Massey University, 1996) Yee, Nigel
    Control system engineering strives to alter a systems performance to suit the objectives of the user. This requires pre-requisite knowledge of the system behaviour. This is often in the form of mathematical models of the system. These models can then be used to simulate the system and obtain a sound understanding of the systems operation, these can then be used in controller design. Every real world physical system has its own unique characteristics. These must be modelled to develop a simulation of the system. The uniqueness of a real world system necessitates the use of experimental practices and procedures to obtain information about the system. This information is then used to form models representing the system. A simulation of the system can then be based on these models. In this project a robotic system comprising of a link structure, a pneumatic driving system and a valve regulating system, is investigated. Mathematical models describing each component of the robotic system are investigated. Mathematical models describing the dynamic interactions of the link structure are developed and implemented in a fashion to facilitate control of the robot mechanism. The equations are in an explicit form which do not require the use of a numerical method for development of state space equations used in controller development. The pneumatic muscle used as the desired actuator for the robot structure is analysed. Analytical models obtained from the available literature are examined and new models are developed to describe the characteristics of the pneumatic muscle. A proto-type valve specially developed for supplying air to the pneumatic muscle is investigated. Experiments are conducted on this valve to characterise the valves behaviour. A model of the valves behaviour is then developed. A selection of controllers are then applied to the valve pneumatic muscle system. The investigation of alternative actuation systems proposes a new rotary pneumatic muscle design. Analytical models for the rotary pneumatic muscle are developed, a prototype is constructed as part of a feasibility study.
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    Real time Visual SLAM for mobile robot navigation and object detection : a thesis presented in partial fulfilment of the requirement for the degree of Doctor of Philosophy in Engineering at Massey University, Albany, New Zealand
    (Massey University, 2017) Jing, Changjuan
    This study developed a real-time Visual Simultaneous Localization and Mapping (SLAM) method for mobile robot navigation and object detection (SLAM-O), in order to establish the position of a mobile robot and interesting objects in an unknown indoor environment. The VEX Robotics Competition (VRC) is one of the largest, fastest growing educational programmes in the world, and it is designed to increase student interest and involvement in Science, Technology, Engineering, and Mathematics (STEM). This study aims to enable an autonomous robot to compete with human participants in the VRC match, where robots are programmed to respond to a user’s remote control. To win the competition, the robot needs to optimise between detection of goal objects, navigation and scoring. This thesis presents a Visual SLAM technique for robot localization and field objects’ mapping, and aims to provide an innovative and practical approach to control robot navigation and maximise its scoring. For visual observation, this study consists of an evaluation and comparison of widely used RGB-D cameras. Also, this thesis describes the integration of an iterated video frames module with the Extended Kalman Filter (EKF) for accurate SLAM estimation; where, a new frame selection method is employed. A novel SLAM-O method is developed for detecting objects in a robot’s navigation process. The SLAM-O method uses a new K-Means-based colour identification method for semi-transparent object detection and a new concave-based object separation method for multi-connected objects, which outperform traditional methods. Through conducting an investigation into RGB-D cameras’ performance, in terms of repeatability and accuracy, colour images and depth point clouds accuracy from different cameras are evaluated and compared. These comparison’s results provide a reference for choosing a camera for robot localisation. Depth errors and covariance are obtained from the investigation. The obtained results provide important parameters for a RGB-D camera related computation, such as a SLAM problem, etc. An Extended Kalman Filter (EKF) based Visual SLAM method and an iterated video frames module integrated in the EKF are developed. The Visual SLAM method can handle feature detection and corresponding depth measurements in an efficient way, and the iterated video frames module is capable of maximise robot self-localization accuracy. Experimental results demonstrate the accuracy of states estimate. These two method enables a mobile robot navigates accurately in an indoor environment with low computation cost. In addition, this study also presents a SLAM-O method by integrating object detection into Visual SLAM. SLAM-O enables robots to locate objects of interest, which can be used in robotic applications, such as navigation, object grasp, etc. To locate objects which are semi-transparent or closely connected, a K-Means method to clustering pixels on a semi-transparent object’s surface and a concave based method for object separation are developed. Experimental results prove the methods efficiency. These two methods are efficient and useful tools for object detection in SLAM-O framework.
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    Automatic calibration of a video camera lens system : a thesis presented in partial fulfilment of the requirements for the degree of Master of Technology in Information Engineering at Massey University
    (Massey University, 1997) Hunt, Christopher Louis
    An automated camera calibration procedure was successfully developed to allow accurate measurements to be made from images obtained from camera-lens systems exhibiting geometric and lens distortion. The calibration procedure is based upon image analysis methods programmed in script using Mathworks MATLAB software. The process initially involved capturing an 512 x 512 pixel image of a calibration chart consisting of a regularly spaced two dimensional grid of circle shaped fiducial marks. Background leveling was used to correct intensity gradients due to non uniform illumination. A region of interest was determined for each fiducial mark in the image, by thresholding followed by an identification process. A grayscale Centroid Calculation Method was then used to accurately determine the center position of each fiducial mark. Two polynomial equations were fitted in the least squares sense to describe an inverse spatial transformation function that mapped fiducial mark position (xT,yT) in the image to the actual positions (x,y) in real world coordinates on the calibration chart. A second image of a calibration chart was obtained so that the overall calibration error could be assessed for the procedure. The effect of altering the degree of the fitted polynomial equation on the error was investigated. No significant reduction in error was achieved by increasing the order of the fitted polynomial equations above order 4. The effect of altering fiducial mark size on error was investigated. For the Fujinon TV lens being tested at a focal distance of 32 cm and a field size of approximately 18 cm square, an optimal fiducial mark diameter was determined to be 3 mm (8.5 pixels). Increased calibration error was obtained for fiducial mark diameters both greater and less than this figure. The effects on calibration error of varying aperture were investigated. Greater calibration error observed at low aperture settings was attributed to primary lens aberration and also the possibility of systematic error in the Centroid Calculation Method due to spatial undersampling in the image. Increased diffraction resulting in loss of definition at the reduced aperture probably explains the increase in error that was observed at aperture setting, f22. An optimum aperture setting of f11 was determined, for this particular lens. The use of this camera calibration procedure has resulted in a large increase in accuracy for position determination or measurement from an image. When the non-linear effects of geometric or lens distortion are ignored, the maximum observed error was seen to be as high as 5.10 pixels compared to the maximum error in a 4th order calibrated image of 0.77 pixels. Mean error was observed to decrease from 1.25 to 0.33 pixels in the calibrated case. The mean error obtained as a result of the calibration closely approached the estimated uncertainty present in the physical calibration chart. The computation time required for the calibration of an image of a control chart having 320 control points, including the calculation of a verification image, was found to be 6.5 minutes on a Pentium 100MHz computer. The advantage of the automated procedure is that it is accurate and fast, unlike manual methods that are tedious, time consuming and prone to error.
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    Design and development of a modular framework to integrate sensors and actuators : a thesis presented in partial fulfilment of the requirements for the degree of Masters of Engineering in Mechatronics at Massey University, Manawatu, New Zealand
    (Massey University, 2016) Taylor, Brendan
    This thesis details the research and development of a versatile electronic monitoring and control platform, influenced by the Internet of Things (IoT), mass configurability, modularity, expandability and ease of use. The generic framework which has been designed and tested aims to provide a platform to build a wide variety of specialised systems to integrate sensors and actuators. A central processing unit manages modular hardware devices connected by a serial network. Only the required hardware units are chosen to constitute a system for an application. The processing unit uses modular task handlers to manage the system. The web-based user interface provides multi-platform system access using a web browser. The website is dynamically generated from the system configuration. While the framework is generic, for testing its efficacy, it was applied to a seed and fertilizer spreader to monitor and control the application rate. This application requires coordinated control of actuators using inputs from multiple sources, including sensors, machine states, a database, other processing tasks, and the operator. The implementation was successful in achieving reliable control of the seeding rate, based on the tractor ground speed. The practical implementation exhibited a high level of expandability and modularity. The prototype system has also highlighted a few issues which can be addressed in future revisions to improve the versatility and robustness of the framework.
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    Neural network model predictive control of a ultra high temperature milk treatment plant : a thesis presented in partial fulfilment of the requirements for the degree of Master of Technology in Engineering and Automation at Massey University
    (Massey University, 1997) Karla, Venkateswara Rao
    This thesis reports the development of a Model Predictive Control system for a Ultra High Temperature milk treatment pilot plant. This control system utilises an Artificial Neural Network model of the plant dynamics. The entire process was divided into two parts for modelling purposes. Separate models were trained; one for simulating the dynamics of the hot water heating loop and the second the dynamics of the heat exchanger circuit. The two sub-models, when concatenated, form a complete model of the plant referred to as a composite neural network model. The results of training and testing of the sub-models with various sets of plant data were presented. Of all the possible combination of sub-models, the best trained and tested sub-models were concatenated to form the best composite network model, and the combination of worst sub-models to form worst composite network model. Two model predictive control (MPC) systems for the process were developed, one using the best composite network model for prediction purposes and to act as the plant, and the other using the worst composite model for prediction and best composite model as the plant. Both the developed MPC systems were evaluated in terms of setpoint tracking and disturbance rejection. As a part of these performance tests, a PI (Proportional-Integral) control system of the UHT plant was developed in a simulated environment using the best composite neural network model to act as the plant. The responses of both the MPC control systems were studied and compared with the responses of the PI control system.
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    Design and development of a robotic tape applicator : a thesis presented in partial fulfilment of the requirements for the degree of Master of Technology in Manufacturing and Industrial Technology at Massey University
    (Massey University, 1996) Guntur, Murali
    The work described in this thesis is on the design, operation and testing of a programmable adhesive tape applicator 'EziStick'. The system demonstrates a mechatronics system comprised of mechanical, electronic and computer systems. 'EziStick' is capable of identifying any tape edge and then initialising and loading the tape over the applicator foot for successful application of tape. The tape tension monitoring system will allow continuous monitoring of the tape tension during its application. 'EziStick' is currently attached to the end of a robot arm to enhance its work envelope. The system is controlled via a low cost microcontroller and it is highly modular and transportable. 'EziStick' may be attached to the end of any robot (machines) with various degrees of freedom. In this way the cost of the system is adjusted by the complexity of the application. The experimental results showed that there is a relationship between the tape application speed and the quality of its application. Although the current prototype is designed for the application of aluminium tape, tests have indicated that other types of tape can be used in 'EziStick'.