The Coordinate Measuring Machine (CMM) is a key improving the reliability and quality of production. During operation, however, collision between the CMM, probe system, and parts may result in costly damage. Avoiding potential collisions is always an important issue for CMM inspection. This thesis reports design and implementation of an online collision detection system for CMMs. Compared to previous offline collision detection implementations, the new online collision detection system can react to potential collision situations in real time. The collision avoidance system architecture and algorithms are described in this thesis. Each possible CMM translation and probe rotation case is considered. Every component in this system is connected by certain communication protocol and distributed on different computers according to the requirements of applications. This design brings more flexibility to this system. The system components for inspection path planning, collision detection, and CMM motion control are distributed to separate computers, with a TCP/IP based protocol used for communication. This modular, component based design provides more flexibility. / Thesis / Master of Applied Science (MASc)

Cheung, Lap Chi. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2007. / Includes bibliographical references (leaves 91-95). / Abstracts in English and Chinese. / Chapter 1. --- INTRODUCTION --- p.1 / Chapter 1.1. --- Background --- p.1 / Chapter 1.1.1. --- Introduction to Intelligent Vehicle --- p.1 / Chapter 1.1.2. --- Typical Vehicle Tracking Systems for Rear-end Collision Avoidance --- p.2 / Chapter 1.1.3. --- Passive VS Active Vehicle Tracking --- p.3 / Chapter 1.1.4. --- Vision-based Vehicle Tracking Systems --- p.4 / Chapter 1.1.5. --- Characteristics of Computing Devices on Vehicles --- p.5 / Chapter 1.2. --- Motivation and Objectives --- p.6 / Chapter 1.3. --- Major Contributions --- p.7 / Chapter 1.3.1. --- A 3-phase Vision-based Vehicle Tracking Framework --- p.7 / Chapter 1.3.2. --- Camera-to-vehicle Distance Measurement by Single Camera --- p.9 / Chapter 1.3.3. --- Real Time Vehicle Detection --- p.10 / Chapter 1.3.4. --- Real Time Vehicle Tracking using Simplified Image Alignment --- p.10 / Chapter 1.4. --- Evaluation Platform --- p.11 / Chapter 1.5. --- Thesis Organization --- p.11 / Chapter 2. --- RELATED WORK --- p.13 / Chapter 2.1. --- Stereo-based Vehicle Tracking --- p.13 / Chapter 2.2. --- Motion-based Vehicle Tracking --- p.16 / Chapter 2.3. --- Knowledge-based Vehicle Tracking --- p.18 / Chapter 2.4. --- Commercial Systems --- p.19 / Chapter 3. --- 3-PHASE VISION-BASED VEHICLE TRACKING FRAMEWORK --- p.22 / Chapter 3.1. --- Introduction to the 3-phase Framework --- p.22 / Chapter 3.2. --- Vehicle Detection --- p.23 / Chapter 3.2.1. --- Overview of Vehicle Detection --- p.23 / Chapter 3.2.2. --- Locating the Vehicle Center - Symmetrical Measurement --- p.25 / Chapter 3.2.3. --- Locating the Vehicle Roof and Bottom --- p.28 / Chapter 3.2.4. --- Locating the Vehicle Sides - Over-complete Haar Transform --- p.30 / Chapter 3.3. --- Vehicle Template Tracking Image Alignment --- p.37 / Chapter 3.3.5. --- Overview of Vehicle Template Tracking --- p.37 / Chapter 3.3.6. --- Goal of Image Alignment --- p.41 / Chapter 3.3.7. --- Alternative Image Alignment - Compositional Image Alignment --- p.42 / Chapter 3.3.8. --- Efficient Image Alignment - Inverse Compositional Algorithm --- p.43 / Chapter 3.4. --- Vehicle Template Update --- p.46 / Chapter 3.4.1. --- Situation of Vehicle lost --- p.46 / Chapter 3.4.2. --- Template Filling by Updating the positions of Vehicle Features --- p.48 / Chapter 3.5. --- Experiments and Discussions --- p.49 / Chapter 3.5. 1. --- Experiment Setup --- p.49 / Chapter 3.5.2. --- Successful Tracking Percentage --- p.50 / Chapter 3.6. --- Comparing with other tracking methodologies --- p.52 / Chapter 3.6.1. --- 1-phase Vision-based Vehicle Tracking --- p.52 / Chapter 3.6.2. --- Image Correlation --- p.54 / Chapter 3.6.3. --- Continuously Adaptive Mean Shift --- p.58 / Chapter 4. --- CAMERA TO-VEHICLE DISTANCE MEASUREMENT BY SINGLE CAMERA --- p.61 / Chapter 4.1 --- The Principle of Law of Perspective --- p.61 / Chapter 4.2. --- Distance Measurement by Single Camera --- p.62 / Chapter 5. --- REAL TIME VEHICLE DETECTION --- p.66 / Chapter 5.1. --- Introduction --- p.66 / Chapter 5.2. --- Timing Analysis of Vehicle Detection --- p.66 / Chapter 5.3. --- Symmetrical Measurement Optimization --- p.67 / Chapter 5.3.1. --- Diminished Gradient Image for Symmetrical Measurement --- p.67 / Chapter 5.3.2. --- Replacing Division by Multiplication Operations --- p.71 / Chapter 5.4. --- Over-complete Haar Transform Optimization --- p.73 / Chapter 5.4.1. --- Characteristics of Over-complete Haar Transform --- p.75 / Chapter 5.4.2. --- Pre-compntation of Haar block --- p.74 / Chapter 5.5. --- Summary --- p.77 / Chapter 6. --- REAL TIME VEHICLE TRACKING USING SIMPLIFIED IMAGE ALIGNMENT --- p.78 / Chapter 6.1. --- Introduction --- p.78 / Chapter 6.2. --- Timing Analysis of Original Image Alignment --- p.78 / Chapter 6.3. --- Simplified Image Alignment --- p.80 / Chapter 6.3.1. --- Reducing the Number of Parameters in Affine Transformation --- p.80 / Chapter 6.3.2. --- Size Reduction of Image A ligmnent Matrixes --- p.85 / Chapter 6.4. --- Experiments and Discussions --- p.85 / Chapter 6.4.1. --- Successful Tracking Percentage --- p.86 / Chapter 6.4.2. --- Timing Improvement --- p.87 / Chapter 7. --- CONCLUSIONS --- p.89 / Chapter 8. --- BIBLIOGRAPHY --- p.91

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This paper presents algorithms for computing constraints on the position of an object due to the presence of obstacles. This problem arises in applications which require choosing how to arrange or move objects among other objects. The basis of the approach presented here is to characterize the position and orientation of the object of interest as a single point in a Configuration Space, in which each coordinate represents a degree of freedom in the position and/or orientation of the object. The configurations forbidden to this object, due to the presence of obstacles, can then be characterized as regions in the Configuration Space. The paper presents algorithms for computing these Configuration Space obstacles when the objects and obstacles are polygons or polyhedra. An approximation technique for high-dimensional Configuration Space obstacles, based on projections of obstacles slices, is described.

There are various kinds of creature living in the world and each kind of creatures has its own unique life habits and behavior patterns. For these reasons between the creature as well as the biology and the environment can have many interactions with each other, and we may observe these interactions easily in the frequently daily life. However the humanity may be the quantity hugest, and also have the most complex behavior at the fine race group in all kind of creatures on earth. So how could we penetrate into by observed and analysis to obtain the information which translates to the computer simulation realistically is a topic of the very hardship with challenge to presents the human behavior. Virtually all previous work has been agent-based, meaning that motion is computed separately for each individual. Such models can capture each person¡¦s unique situation. So the agent-based modeling will inevitably result in a large number of calculation and make poor efficiency. In addition, there are leader-follower system which consists of a leader and multiple followers. This leader will lead the entire group to the destination, and the followers will follow the motion of their leader closely. In our research apply the physical properties of electric charge to the simulation of pedestrians by using the basic concepts of electromagnetism. The simulation method contains the agent-based modeling and the leader-follower system at the same time. The agent-based modeling simulates pedestrian of the individual motion. The goal of the leader-follower system is to simulate the real world behavior that people in a community often move by following a specific object.

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This thesis documents an investigation into the automatic provision of reasonably realistic motion for the computer generated target ships in a marine simulator. The thesis explores: automatic collision avoidance between the target ships; automatic track keeping for the target ships; the use of sea stabilised and land stabilised motion for the target ships; some issues of software fault tolerance in marine simulators; message frameworks for use in a Multi-Agent System (MAS) simulation; the opportunity to provide different manoeuvring characteristics for different target ships; and the use of autonomous agents to control the target ships. A software system has been developed to facilitate this research. Entitled "A Multi-Agent Realm for Investigating Navigators' Educational Simulators" (MARINES), the software is a MAS providing much of the functionality of a marine simulator instructor station; basic functions are encapsulated into the instructor environment and additional features are provided by processes that connect to the environment using Dynamic Data Exchange. The processes can also connect to each other and, in MARINES, co-operate to navigate the ships. These co-operative, autonomous processes are the agents that together form a MAS. A simple 3D view is also connected, enabling the view from the bridge of a specific target ship to be assessed. The MARINES software is written using C++ to run under Microsoft Windows v3.1. Therefore, the processes multi-task co-operatively. In MARINES each target ship can be made to perform in an individual manner; manoeuvring and performance characteristics can be customised to simulate a specific ship type. Additionally, the agents performing collision avoidance can be given rule sets that interpret the International Regulations for the Prevention of Collisions at Sea in subtly different ways, and the track-keeping agents can have different beliefs about the manoeuvring capabilities of the vessels they control. Automatic collision avoidance and track keeping is performed for two-ship situations even when the set and drift of a current is introduced. A comparison is made with the tracks of land stabilised targets. This shows how aspect, course and speed are affected by ignoring the effects of the current, and demonstrates the need for an accurate simulation.

As UASs (Uncrewed Aerial System) are further integrated into operations, the need for on-board environmental perception and sensing is necessitated. An accurate and reliable creation of a 3D map resembling an aircraft's surrounding is crucial for accurate collision avoidance and path planning. Consumer UASs are now being equipped with sensors to fulfill such a requirement – but no system has been proven as capable of being fully relied upon. With many sensing options available, there are several constraints regarding size, weight, and cost that must be considered when developing a sensing solution. Additionally, the robustness of the system must not be diminished when moving to a system that minimizes size, weight, or cost. An analysis of different sensing technologies that small rotary-wing aircraft (below 25kg) can be outfitted with for collision avoidance is performed. Several sensing technologies are initially compared through technology analyses and controlled experiments. The topmost systems were then further integrated onto a small low-cost quadcopter for flight testing and data acquisition. Ultimately, a fusion between stereo vision imagery and radar was deemed the most reliable method for providing environmental data needed for collision avoidance. / Master of Science / As drones become further integrated in several industries, it is important that their operations are conducted in a safe manner. Most drones today have a limited ability to sense and react to the environment around them. This results in the risk of the drone colliding with people or obstacles such as buildings, trees, light poles, etc. Thus, an accurate and reliable creation of a 3D map resembling a drone's surrounding is crucial for collision avoidance. This would allow for the avoidance of people and obstacles during automated flights where the drone may encounter obstacles during flight. With many sensing options available, there are several constraints regarding size, weight, and cost that must be considered when developing a sensing solution. Additionally, the reliability of the system must be of the topmost priority to ensure safe operations. An analysis of different sensing technologies that small rotary-wing aircraft (below 25kg) can be outfitted with for collision avoidance is performed. Rotary-wing aircraft are a specific subset of drones that are capable of vertical takeoff, landing, and hover (i.e not planes). An analysis regarding the several sensing technologies was first conducted to select the three topmost solutions. These solutions were then integrated onto a small low-cost quadcopter for data collection and flight testing. Ultimately, a combination of stereo vision imagery and radar was deemed the most reliable method for collecting collision avoidance data.

ITC/USA 2008 Conference Proceedings / The Forty-Fourth Annual International Telemetering Conference and Technical Exhibition / October 27-30, 2008 / Town and Country Resort & Convention Center, San Diego, California / UUV homing and docking and UAV collision avoidance are two seemingly separate research topics for different applications. Upon close examination, these two are a pair of dual problems, with interesting correspondences and commonality. In this paper, we present the theoretical analysis, signal processing, and the field experiments of these two algorithms in UAV and UUV applications in homing and docking as well as collision avoidance.