No description available.

No description available.

No description available.

No description available.

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

A Finite Hilbert Basis Set (FHBS) method to calculate the angular and energy distribution of ejected electrons in an ion-atom collision is presented. This method has been applied to the p + H collision at 20 keV impact energy. An interference effect between the exit channels, where electrons are guided out of the collision region by both the residual target proton and the projectile proton, is discovered. Experimental data appears to confirm this result.

This research work focused on studying the emission spectroscopy produced from the high energy ion-molecule collision processes in mass spectrometry. The collision experiments are described and divided into 4 chapters (Chapter 3, 4, 5, 6).N2O+● is an ion of atmospheric importance. In chapter 3 the investigation of the collision between high translational energy (4-8 keV range) N2O+● ions and Helium target gas in mass spectrometry using collision induced emission (CIE) spectroscopy is described.In chapter 4, the collision-induced emission (CIE) spectra from 4-8 keV collisions between projectile He+● ions and CO2 target gas (He+●/CO2) were obtained. In Chapter 5, to probe the validity of this hypothesis, CIE experiments were carried out to observe the photon emissions from keV collisions of a selection of projectile ions with O2 target gas. By studying the resulting CIE spectra, a second potential mechanism came to light, one that involves the nearly isoenergetic O2+. A → X state transition. In chapter 6, neutral hydroxymethylene and formaldehyde were generated by charge exchange neutralization of their respective ionic counterparts and then were reionized and detected as recovery signals in neutralization-reionization mass spectrometry in the modified VG-ZAB mass spectrometer.

This research work focused on studying the emission spectroscopy produced from the high energy ion-molecule collision processes in mass spectrometry. The collision experiments are described and divided into 4 chapters (Chapter 3, 4, 5, 6).N2O+● is an ion of atmospheric importance. In chapter 3 the investigation of the collision between high translational energy (4-8 keV range) N2O+● ions and Helium target gas in mass spectrometry using collision induced emission (CIE) spectroscopy is described.In chapter 4, the collision-induced emission (CIE) spectra from 4-8 keV collisions between projectile He+● ions and CO2 target gas (He+●/CO2) were obtained. In Chapter 5, to probe the validity of this hypothesis, CIE experiments were carried out to observe the photon emissions from keV collisions of a selection of projectile ions with O2 target gas. By studying the resulting CIE spectra, a second potential mechanism came to light, one that involves the nearly isoenergetic O2+. A → X state transition. In chapter 6, neutral hydroxymethylene and formaldehyde were generated by charge exchange neutralization of their respective ionic counterparts and then were reionized and detected as recovery signals in neutralization-reionization mass spectrometry in the modified VG-ZAB mass spectrometer.

A Finite Hilbert Basis Set (FHBS) method to calculate the angular and energy distribution of ejected electrons in an ion-atom collision is presented. This method has been applied to the p + H collision at 20 keV impact energy. An interference effect between the exit channels, where electrons are guided out of the collision region by both the residual target proton and the projectile proton, is discovered. Experimental data appears to confirm this result.

<p>This master's thesis presents the development of a collision handling function for Motoman industrial robots and investigates further use of the developed software. When a collision occurs the arm is to be retracted to a safe home location and the job is to be restarted to resume the production. The retraction can be done manually, which demands that the operator has to have good knowledge in robot handling and it might be a time consuming task. To minimise the time for restarting the job after a collision and allowing employees that have limited knowledge in robot handling to retract and restart the job, Motoman provides an automatical retraction function. However, the retraction function may cause further collisions when used and therefor a new function for retracting the arm is needed. The new function is based on that the motion of the robot is recorded by sampling the servo values, which are then stored in a buffer. A job file is automatically created and loaded into the control system, and the position variables of the job file are updated using the contents of the buffer. This will ensure a safe retraction of the arm as long as the environment surrounding the robot remains the same.</p><p>The developed software made it possible to control the robot in real-time by changing the buffer information, which has lead to a cognitive system called the Pathfinder. By initiating the Pathfinder function with at least a start and an end point, the function generates a collision free path between the start point and the end point. A pilot-study has also been made concerning integration of a vision system with the Pathfinder to increase the decision handling for the function.</p>