La détection de collision est une tâche essentielle pour la simulation physique d’environnements virtuels. De nos jours, la détection de collision est l’un des goulets d’étranglement calculatoire dans les applications de réalité virtuelle dû à la complexité des environnements que l’on souhaite simuler et par la contrainte d’interaction en temps-réel. Nous avons concentré nos travaux sur la seconde étape de la détection de collision (narrow-phase) dans laquelle les tests de collisions sont effectués sur des paires d’objets. Contrairement à la première étape, les tests de collisions sont effectués sur des versions détaillées des modèles géométriques et sont donc très sensible au niveau calculatoire à la complexité géométrique de ceux-ci.Cette thèse vise à améliorer les performances de la détection de collision lors de l’utilisation d’objets géométriques complexes (formes représentées par un maillage, éventuellement non-convexe et/ou déformable). Nos méthodes permettent d’accélérer le calcul de la narrow-phase. Les algorithmes proposés peuvent être implémentés sur GPU pour profiter de leur puissance de calcul et ainsi améliorer les performances.Pour réaliser la narrow-phase, nous proposons un pipeline adapté à une implémentation GPU. Celui-ci permet de réaliser la narrow-phase à l’aide d’algorithmes basés lancer de rayon. Notre méthode repose sur un principe commun où tous les tests de collision sont effectués par lancer de rayon à partir des sommets des objets. Cette généricité nous permet de réaliser les tests sur des maillages ayant n’importe quelles propriétés (rigide ou déformable, convexe ou non-convexe). Les algorithmes de lancer de rayon utilisés étant choisis en fonction des propriétés des objets pour optimiser les performances.Nous avons généralisé la méthode de détection de collision utilisée pour supporter, en plus des objets volumiques, des objets surfaciques (tels que des tissus). Cette méthode est compatible avec le pipeline proposé et permet de réaliser des tests de collisions entre n’importe quelle combinaison d’objets.De plus, nous proposons d’exploiter la cohérence temporelle pour améliorer les performances. Le résultat de la détection de collision est généralement très semblable entre deux pas de temps successifs. Suite à cette observation, nous proposons un algorithme de lancer de rayon itératif qui intègre le résultat du pas précédent pour exploiter cette cohérence temporelle. Cet algorithme peut être utilisé conjointement avec des algorithmes de lancer de rayon standard. Il permet de remplacer certains tests unitaires pour mettre à jour de manière incrémentale le résultat de la détection de collision. L’algorithme de lancer de rayon itératif est ajouté au pipeline en tant qu’alternative aux autres algorithmes de lancer de rayon et est utilisé prioritairement dû à son faible coût calculatoire. / Collision detection is an essential task for physical simulation of virtual environments. Nowadays, collision detection is one of the main bottleneck of virtual reality applications. This is due to the complexity of the environments we want to simulate and the real-time interaction constraint. We have concentrated our work on the second phase of collision detection, the narrow-phase, in which collision queries are performed on pairs of objects. Contrary to the first phase of collision detection, collision queries are performed on the full representation of the objects (with all details) and are thus sensible to the geometric complexity of the objects in term of computation time.This thesis is aimed to improve the performances of collision detection when using geometrically complex objects (represented with triangle meshes, potentially non-convex and deformable). Our methods are able to reduce computation times. Our proposed algorithms can be implemented on GPU to take advantage of their computational power and thus further improve the performances of our methods.To implements our narrow-phase, we propose a pipeline which is adapted for GPU execution. This pipeline perform collision detection with ray-tracing algorithms. Our methods rely on a shared principle where all collision queries are performed by casting rays from the vertices of the objects. This genericity allow us to perform collision detection on triangle meshes with any properties (rigid or deformable, convex or non-convex). The ray-tracing algorithms used are dynamically selected depending on the properties of the objects to improve the performances.We have generalized the collision detection method we use in our pipeline to handle, in addition to volumetric objects (represented by their surface), surface objects (such as cloth). This method is compatible with our pipeline and allow us to perform collision detection with any combination of volumetric and surface objects.Furthermore, we propose to exploit temporal coherency to improve performances. The result of collision queries (contact points) are generally similar between successive time-step. Starting from this observation, we propose a ray-racing algorithm which use the result of the previous time-step to exploit this temporal coherency. This ray-tracing algorithm can be used in conjunction to standard ray-tracing algorithms. It is used to replace standard ray-tracing algorithms in specific condition to update the result of the previous time-step instead of computing it from scratch. The iterative ray-tracing algorithm is added in our pipeline as an alternative to other ray-tracing algorithms and is used in priority due to his lower computational cost compared to other algorithms.

In this project, a novel human friendly mobile robot navigation controller is investigated. By applying this controller, the mobile robot is able to work in a complicated environment with several humans and other obstacles avoiding them before a collision happens. This robot will have a preference in avoiding humans over other obstacles keeping human safety as its first consideration. To achieve this goal, three problems have to be solved. The first one is the robot should be able to “see” the environment and distinguish the human and the obstacles. The functions of human sensor and sonar sensor are presented. A new sensor fusion method for combining the information collected by these two sorts of sensors based on Dempster-Shafer evidence theory is also proposed. By using the sensor fusion method, the robot will have a better view of human. The second problem is the robot has to know how to avoid collision. A new navigation algorithm, based on an improved velocity potential field method, is then described. The way of calculating the distances of avoidance based on different kinds of obstacles is presented as well. The last problem is how to make the mobile robot put human as its first priority when avoiding collision. A summary of the methods which are used to protect human is mentioned. According to the simulation and the experimental results, the new mobile robot navigation controller successfully led the robot avoid collisions in complicated situations and always put human safety as its first consideration.

Piecewise smooth maps appear as models of various physical, economical and other systems. In such maps bifurcations can occur when a fixed point or periodic orbit crosses or collides with the border between two regions of smooth behaviour as a system parameter is varied. These bifurcations have little analogue in standard bifurcation theory for smooth maps and are often more complex. They are now known as "border collision bifurcations". The classification of border collision bifurcations is only available for one-dimensional maps. For two and higher dimensional piecewise smooth maps the study of border collision bifurcations is far from complete. In this thesis we investigate some of the bifurcation phenomena in two-dimensional continuous piecewise smooth discrete-time systems. There are a lot of studies and observations already done for piecewise smooth maps where the determinant of the Jacobian of the system has modulus less than 1, but relatively few consider models which allow area expansions. We show that the dynamics of systems with determinant greater than 1 is not necessarily trivial. Although instability of the systems often gives less useful numerical results, we show that snap-back repellers can exist in such unstable systems for appropriate parameter values, which makes it possible to predict the existence of chaotic solutions. This chaos is unstable because of the area expansion near the repeller, but it is in fact possible that this chaos can be part of a strange attractor. We use the idea of Markov partitions and a generalization of the affine locally eventually onto property to show that chaotic attractors can exist and are fully two-dimensional regions, rather than the usual fractal attractors with dimension less than two. We also study some of the local and global bifurcations of these attracting sets and attractors.Some observations are made, and we show that these sets are destroyed in boundary crises and some conditions are given.Finally we give an application to a coupled map system.

A large percentage of automobile accidents in city traffic occur at speeds below 15 mph. Unfortunately there is a scarcity of experimental crash data at these low speeds to help investigators to reconstruct accidents. Accident reconstruction experts have consequently attached a low level of confidence to speed predictions from vehicle crush at the low end of the speed spectrum. The need for more experimental crash data, especially in a low speed range, has repeatedly been mentioned by accident investigators. The University of British Columbia Accident Research Croup has constructed a crash test facility in conjunction with the Insurance Corporation of British Columbia to address this need. The lCBC-UBC barrier is a low speed crash test facility. A description of the ICBC-UBC crash barrier, its systems and crash testing techniques at the ICBC-UBC facility are presented in this thesis. Also multiple impacts on the same vehicle are investigated to see if this technique provided accumulated crush data that reproduced known high speed crashes. In addition, the preliminary findings are presented on the impact speed to initiate permanent crush and subsequent implications toward vehicle crush characteristics in a low speed range. / Applied Science, Faculty of / Civil Engineering, Department of / Graduate

Vehicle collisions with bridge piers can result in significant damage to the support pier and potentially lead to catastrophic failure of the whole structure. The Nation’s aging infrastructure suggests that many structures no longer meet current design standards, placing many bridge susceptible to failure if subjected to an extreme loading event. This research aims to study the structural response of reinforced concrete bridge piers subjected to vehicle collisions. A sensitivity analysis is conducted to observe the causes of shear and bending failures of bridge piers subjected to vehicle collision. Parameters, such as pier diameter, transverse reinforcement spacing, vehicle impact velocity, pile cap height, and multi-pier configuration, are investigated in this study. The finite element code LS-DYNA is utilized to simulate and analyze the vehicle collisions to obtain accurate and detailed results. The vehicle models offered by the National Crash Analysis Center and the National Transportation Research Center, Inc. are used to conduct this research. The finite element modeling controls and material properties are validated by conducting an impact drop hammer experiment. The bridge pier collision models are validated by comparing vehicle damage and impact forces with published research results. Conservation of energy is also checked to assure stability within the impact simulation. A sensitivity analysis suggests that different pier parameters have a profound effect on failure modes and distribution of impact forces. Piers with large stiffness result in high impact forces, low lateral displacements, and high resistance to shear forces and bending moments. A performance-based analysis shows that bridge piers can be designed using damage ratios associated with particular damage states.

<p>This study describes a fast approach using GPU to process self-collision in cloth animation without significant compromise in physical accuracy. The proposed fast approach is built and works effectively on a modification of Mass Spring Model which is seen in a variety of cloth simulation study. Instead of using hierarchical data structure which needs to be updated each frame, this fast approach adopts a spatial hashing technique which virtually partitions the space where the cloth object locates into small cubes and stores the information of the particles being held in the cells with an integer array. With the data of the particles and the cells holding information of the particles, self-collision detection can be processed in a very limited cost in each thread launched in GPU regardless of the increase in the amount of particles. This method is capable of visualizing self-collision detection and response in real time with limited cost in accessing memory on the GPU. </p> <p>The idea of the proposed fast approach is extremely straightforward, however, the amount of memory which is needed to be consumed by this method is its weakness. Also, this method sacrifices physical accuracy in exchange for the performance.</p>

The topic of this thesis is on-board estimation of spacecraft collision probability for orbital rendezvous and proximity operations. All of the examples shown in this work assume that the satellite dynamics are described by the Clohessy-Wiltshire equations, and that the spacecraft are spherical. Several collision probability metrics are discussed and compared. Each metric can be placed into one of three categories. The first category provides an estimate of the instantaneous probability of collision, and places an upper bound on the total probability of collision. The second category provides an estimate of total collision probability directly. The last category uses Monte Carlo analysis and a novel Pseudo Monte Carlo analysis algorithm to determine total collision probability. The metrics are compared and their accuracy is determined for a variety of on-orbit conditions. Lastly, a method is proposed in which the metrics are arranged in a hierarchy such that those metrics that can be computed quickest are calculated first. As the proposed algorithm progresses the metrics become more costly to compute, but yield more accurate estimates of collision probability. Each metric is compared to a threshold value. If it exceeds the limits determined by mission constraints, the algorithm computes a more accurate estimate by calculating the next metric in the series. If the threshold is not reached, it is assumed there is a tolerable collision risk and the algorithm is terminated. In this way the algorithm is capable of adapting to the level of collision probability, and can be sufficiently accurate without needless calculations being performed. This work shows that collision probability can be systematically estimated.

First, I attempt to present a unified approach to the study of transport phenomena in multicoponent anisotropic space plasmas. In the limit of small temperature anisotropies this system of generalized transport equations reduces to Grad's 13-moment system of transport equations. In the collisionless limit, the generalized transport equations account for collisionless heat flow, cillisionless viscosity, and large temperature anisotropies. Also, I show that with the appropriate assumptions, the system of generalized transport equations reduces to all of the other major systems of transport equations for anisotropic plasmas that have been derived to date. Next, for application to aeronomy and space physics problems involving strongly magnetized plasma flows, I derive momentum and energy exchange collision terms for interpenetrating bi-Maxwellian gases. Collision terms are derived for Coulomb, Maxwell molecule, and constant collision cross section interaction potentials. The collision terms are valid for arbitrary flow velocity differences and temperature differences between the interacting gases as well as for arbitrary temperature anisotropies. The collision terms have to be evaluated numerically and the appropriate coefficients are presented in tables However, the collision terms are also fitted with simplified expressions, the accuracy of which depends on both the interaction potential and the temperature anisotropy. In addition, I derive the closed set of transport equations that are associated with the momentum and energy collision terms. Finally, I study the extent to which Maxwellian and bi-Maxwellian series expansions can describe plasma flows characterized by non-Maxwellian velocity distributions, with emphasis given to modeling the anisotropic character of the distribution function. The problem considered is the steady state flow of a weakly-ionized plasma subjected to homogeneous electric and magnetic fields, and different collision models are used. In the case of relaxation collision model, a closed form expression is found for the ion velocity distribution function, while for more regorous models (polarization and hard sphere) I have to use the Monte Carlo simulation. These provided a basis for determining the adequacy of a given series expansion. I find that, in general, the bi-Maxwellian-based expansions for the velocity distribution function is better suited to describing anisotropic plasmas than the Maxwellian-based expansions. (166 pages)

Indiana University-Purdue University Indianapolis (IUPUI) / Research on robust Pre-Collision Systems (PCS) requires new techniques that will allow a better understanding of the vehicle-pedestrian dynamic relationship, and which can predict pedestrian future movements. Our research analyzed videos from the Transportation Active Safety Institute (TASI) 110-Car naturalistic driving dataset to extract two dynamic pedestrian semantic features. The dataset consists of videos recorded with forward facing cameras from 110 cars over a year in all weather and illumination conditions. This research focuses on the potential-conflict situations where a collision may happen if no avoidance action is taken from driver or pedestrian. We have used 1000 such 15 seconds videos to find vehicle-pedestrian relative dynamic trajectories and pose of pedestrians. Adaptive structural local appearance model and particle filter methods have been implemented and modified to track the pedestrians more accurately. We have developed new algorithm to compute Focus of Expansion (FoE) automatically. Automatically detected FoE height data have a correlation of 0.98 with the carefully clicked human data. We have obtained correct tractography results for over 82% of the videos. For pose estimation, we have used flexible mixture model for capturing co-occurrence between pedestrian body segments. Based on existing single-frame human pose estimation model, we have introduced Kalman filtering and temporal movement reduction techniques to make stable stick-figure videos of the pedestrian dynamic motion. We were able to reduce frame to frame pixel offset by 86% compared to the single frame method. These tractographs and pose estimation data were used as features to train a neural network for classifying ‘potential conflict’ and ‘no potential conflict’ situations. The training of the network achieved 91.2% true label accuracy, and 8.8% false level accuracy. Finally, the trained network was used to assess the probability of collision over time for the 15 seconds videos which generates a spike when there is a ‘potential conflict’ situation. We have also tested our method with TASI mannequin crash data. With the crash data we were able to get a danger spike for 70% of the videos. The research enables new analysis on potential-conflict pedestrian cases with 2D tractography data and stick-figure pose representation of pedestrians, which provides significant insight on the vehicle-pedestrian dynamics that are critical for safe autonomous driving and transportation safety innovations.

Indiana University-Purdue University Indianapolis (IUPUI) / Ion mobility spectrometry is a powerful technique for the study related to molecule. The work of tow major applications are introduced in this paper. The first application is the optimization of parameters in CCS. The accurate calculation of the collision cross section for multiple molecules is a long-time interested topic in the research for substances detection in micro scale. No reliable analytical approach to calculate the collision cross section has been established to date. Different approaches rely on different mechanism will provide different results in significant extent. This work introduce a method for the determination of parameters in the Lennard Jones potential. Experimental data combined with numerical computation was the fundamental strategy during the optimization of the parameters. In the experiment, electrospray is used as the ion source of IMS while a nebulizer was utilized to electrify the aromatic compounds. New parameters show no less accuracy and equal efficiency while can explain the physical meaning of the collision more clearly. The second application is the trace detection of explosives with very low concentration. The detection of explosives is an important topic in security, while the detection will be difficult due to the low vapor pressure of explosives. In this work, two types of devices are designed for the trace detection of explosives at an extremely low concentration. TNT is selected as the explosives in the experiment. The experiment succeed to reach a sensitivity of 1 part per quintillion, and even find out a linear relationship between the logarithm of TNT concentration and TNT vapor pressure.