Efficient Distance Computation Algorithm between Nearly Intersected Objects Using Dynamic Pivot Point in Virtual Environment Application

Finding nearly accurate distance between two or more nearly intersecting three-dimensional (3D) objects is vital especially for collision determination such as in virtual surgeon simulation and real-time car crash simulation. Instead of performing broad phase collision detection, we need to check for accuracy of detection by running narrow phase collision detection. One of the important elements for narrow phase collision detection is to determine the precise distance between two or more nearly intersecting objects or polygons in order to prepare the area for potential colliding. Distance computation plays important roles in determine the exact point of contact between two or more nearly intersecting polygons where the preparation for collision detection is determined at the earlier stage. In this paper, we describes our current works of determining the distance between objects using dynamic pivot point that will be used as reference point to reduce the complexity searching for potential point of contacts. By using Axis-Aligned Bounding Box for each polygon, we calculate a dynamic pivot point that will become our reference point to determine the potential candidates for distance computation. The test our finding distance will be simplified by using our method instead of performing unneeded operations. Our method provides faster solution than the previous method where it helps to determine the point of contact efficiently and faster than the other method.Comment: 6 page

Efficient Distance Computation Algorithm Between Nearly Intersect Objects Using Dynamic Pivot Point In Virtual Environment Application

Finding nearly accurate distance between two or more nearly intersecting three-dimensional (3D) objects is vital especially for collision determination such as in virtual surgeon simulation and real-time car crash simulation. Instead of performing broad phase collision detection, we need to check for accuracy of detection by running narrow phase collision detection. One of the important elements for narrow phase collision detection is to determine the precise distance between two or more nearly intersecting objects or polygons in order to prepare the area for potential colliding. Distance computation plays important roles in determine the exact point of contact between two or more nearly intersecting polygons where the preparation for collision detection is determined at the earlier stage. In this paper, we describes our current works of determining the distance between objects using dynamic pivot point that will be used as reference point to reduce the complexity searching for potential point of contacts. By using Axis-Aligned Bounding Box for each polygon, we calculate a dynamic pivot point that will become our reference point to determine the potential candidates for distance computation. The test our finding distance will be simplified by using our method instead of performing unneeded operations. Our method provides faster solution than the previous method where it helps to determine the point of contact efficiently and faster than the other method

Real-time hybrid cutting with dynamic fluid visualization for virtual surgery

It is widely accepted that a reform in medical teaching must be made to meet today's high volume training requirements. Virtual simulation offers a potential method of providing such trainings and some current medical training simulations integrate haptic and visual feedback to enhance procedure learning. The purpose of this project is to explore the capability of Virtual Reality (VR) technology to develop a training simulator for surgical cutting and bleeding in a general surgery

Self-adapting parallel metric-space search engine for variable query loads

This research focuses on automatically adapting a search engine size in response to fluctuations in query workload. Deploying a search engine in an Infrastructure as a Service (IaaS) cloud facilitates allocating or deallocating computer resources to or from the engine. Our solution is to contribute an adaptive search engine that will repeatedly re-evaluate its load and, when appropriate, switch over to a dierent number of active processors. We focus on three aspects and break them out into three sub-problems as follows: Continually determining the Number of Processors (CNP), New Grouping Problem (NGP) and Regrouping Order Problem (ROP). CNP means that (in the light of the changes in the query workload in the search engine) there is a problem of determining the ideal number of processors p active at any given time to use in the search engine and we call this problem CNP. NGP happens when changes in the number of processors are determined and it must also be determined which groups of search data will be distributed across the processors. ROP is how to redistribute this data onto processors while keeping the engine responsive and while also minimising the switchover time and the incurred network load. We propose solutions for these sub-problems. For NGP we propose an algorithm for incrementally adjusting the index to t the varying number of virtual machines. For ROP we present an ecient method for redistributing data among processors while keeping the search engine responsive. Regarding the solution for CNP, we propose an algorithm determining the new size of the search engine by re-evaluating its load. We tested the solution performance using a custom-build prototype search engine deployed in the Amazon EC2 cloud. Our experiments show that when we compare our NGP solution with computing the index from scratch, the incremental algorithm speeds up the index computation 2{10 times while maintaining a similar search performance. The chosen redistribution method is 25% to 50% faster than other methods and reduces the network load around by 30%. For CNP we present a deterministic algorithm that shows a good ability to determine a new size of search engine. When combined, these algorithms give an adapting algorithm that is able to adjust the search engine size with a variable workload

Positioning articulated figures

Many animation systems rely on key-frames or poses to produce animated sequences of figures we interpret as articulated, e.g. the skeleton of a character. The production of poses is a difficult problem which can be solved by using techniques such as forward and inverse kinematics. However, animators often find these techniques difficult to work with. The work, presented in this thesis, proposes an innovative technique which approaches this problem from a totally different direction from conventional techniques, and is based on Interactive Genetic Algorithms (IGAs). IGAs are evolutionary tools based on the theory of evolution which was first described by Darwin in 1859. They are derived from Genetic Algorithms (GAs) themselves based on the theory of evolution. IGAs have been successfully used to produce abstract pictures, sculptures and abstract animation sequences. Conventional techniques assist the animator in producing poses. On the contrary, when working with IGAs, users assist the computer in its search for a good solution. Unfortunately, this concept is too weak to allow for an efficient exploration of the space of poses as the user requires more control over the evolutionary process. So, a new concept was introduced to let the user specify directly what is of interest, that is a limb or a set of limbs. This information is efficiently used by the computer to greatly enhance the search. Users build a pose by selecting limbs which are of interest. That pose is provided to the computer as a seed to produce a new generation of poses. The degree of similarity is specified directly by the user. Typically, it is small at the beginning and increases as the process reaches convergences. The power of this new technique is demonstrated by two evaluations, one which uses a set of non expert users and another one which uses myself as the sole but expert user. The first evaluation highlighted the high cognitive requirement of the new technique whereas the second evaluation showed that given sufficient training, the new technique becomes much faster than the other two conventional techniques

Geometric guides for interactive evolutionary design

This thesis describes the addition of novel Geometric Guides to a generative Computer-Aided Design (CAD) application that supports early-stage concept generation. The application generates and evolves abstract 3D shapes, used to inspire the form of new product concepts. It was previously a conventional Interactive Evolutionary system where users selected shapes from evolving populations. However, design industry users wanted more control over the shapes, for example by allowing the system to influence the proportions of evolving forms. The solution researched, developed, integrated and tested is a more cooperative human-machine system combining classic user interaction with innovative geometric analysis. In the literature review, different types of Interactive Evolutionary Computation (IEC), Pose Normalisation (PN), Shape Comparison, and Minimum-Volume Bounding Box approaches are compared, with some of these technologies identified as applicable for this research. Using its Application Programming Interface, add-ins for the Siemens NX CAD system have been developed and integrated with an existing Interactive Evolutionary CAD system. These add-ins allow users to create a Geometric Guide (GG) at the start of a shape exploration session. Before evolving shapes can be compared with the GG, they must be aligned and scaled (known as Pose Normalisation in the literature). Computationally-efficient PN has been achieved using geometric functions such as Bounding Box for translation and scaling, and Principle Axes for the orientation. A shape comparison algorithm has been developed that is based on the principle of non-intersecting volumes. This algorithm is also implemented with standard, readily available geometric functions, is conceptually simple, accessible to other researchers and also offers appropriate efficacy. Objective geometric testing showed that the PN and Shape Comparison methods developed are suitable for this guiding application and can be efficiently adapted to enhance an Interactive Evolutionary Design system. System performance with different population sizes was examined to indicate how best to use the new guiding capabilities to assist users in evolutionary shape searching. This was backed up by participant testing research into two user interaction strategies. A Large Background Population (LBP) approach where the GG is used to select a sub-set of shapes to show to the user was shown to be the most effective. The inclusion of Geometric Guides has taken the research from the existing aesthetic focused tool to a system capable of application to a wider range of engineering design problems. This system supports earlier design processes and ideation in conceptual design and allows a designer to experiment with ideas freely to interactively explore populations of evolving solutions. The design approach has been further improved, and expanded beyond the previous quite limited scope of form exploration

Generalized Trackball and 3D Touch Interaction

This thesis faces the problem of 3D interaction by means of touch and mouse input. We propose a multitouch enabled adaptation of the classical mouse based trackball interaction scheme. In addition we introduce a new interaction metaphor based on visiting the space around a virtual object remaining at a given distance. This approach allows an intuitive navigation of topologically complex shapes enabling unexperienced users to visit hard to be reached parts

Discrete element computation : algorithms and architecture

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2001.Includes bibliographical references (leaves 156-166).The Discrete Element Method is a numerical technique used to model physical phenomena through the dynamic interactions of a large number of distinct bodies. The strength of the method lies in its ability to accurately model the behavior of inherently discontinuous media, such as granular, fractured, or powdered materials. The major computational obstacle in discrete element simulation is the automatic detection of contacts between bodies. For large simulations, the complexity of the contact detection process is driven by the general spatial reasoning problem of neighbor searching, in which candidate intersection pairs are selected based on their proximity. Neighbor search algorithms exist that exhibit linear scaling in the number of bodies. These algorithms rely, however, on the assumption of uniformly sized objects. Devaitions from this assuption, inherent in many common physical systems, significantly degrade performance. This thesis presents a new grid-based algorithm which accomodates objects of varying size. A new grid-based neighbor search algorithm, called CGrid, is developed to deal with objects of varying sizes. A generic formulation for any number of dimensions is presented. CGrid scales linearly in the number of bodies, and is less sensitive to object size disparity than existing linear algorithms. By combining performance and robustness, CGrid provides a reliable neighbor search solution for general simulation systems. An architecture for simulation is presented, which is designed to support rapid prototyping and extension development.. The core architecture provides an infrastructure of generic components for simulation management. The simulation object heirarchy is constructed to address the issues associated with developing extension capabilities, and supporting the wide variety of objects and behaviors which can be employed within the Discrete Element Method.by Eric David Perkins.Ph.D

Actuation-Aware Simplified Dynamic Models for Robotic Legged Locomotion

In recent years, we witnessed an ever increasing number of successful hardware implementations of motion planners for legged robots. If one common property is to be identified among these real-world applications, that is the ability of online planning. Online planning is forgiving, in the sense that it allows to relentlessly compensate for external disturbances of whatever form they might be, ranging from unmodeled dynamics to external pushes or unexpected obstacles and, at the same time, follow user commands. Initially replanning was restricted only to heuristic-based planners that exploit the low computational effort of simplified dynamic models. Such models deliberately only capture the main dynamics of the system, thus leaving to the controllers the issue of anchoring the desired trajectory to the whole body model of the robot. In recent years, however, we have seen a number of new approaches attempting to increase the accuracy of the dynamic formulation without trading-off the computational efficiency of simplified models. In this dissertation, as an example of successful hardware implementation of heuristics and simplified model-based locomotion, I describe the framework that I developed for the generation of an omni-directional bounding gait for the HyQ quadruped robot. By analyzing the stable limit cycles for the sagittal dynamics and the Center of Pressure (CoP) for the lateral stabilization, the described locomotion framework is able to achieve a stable bounding while adapting to terrains of mild roughness and to sudden changes of the user desired linear and angular velocities. The next topic reported and second contribution of this dissertation is my effort to formulate more descriptive simplified dynamic models, without trading off their computational efficiency, in order to extend the navigation capabilities of legged robots to complex geometry environments. With this in mind, I investigated the possibility of incorporating feasibility constraints in these template models and, in particular, I focused on the joint torques limits which are usually neglected at the planning stage. In this direction, the third contribution discussed in this thesis is the formulation of the so called actuation wrench polytope (AWP), defined as the set of feasible wrenches that an articulated robot can perform given its actuation limits. Interesected with the contact wrench cone (CWC), this yields a new 6D polytope that we name feasible wrench polytope (FWP), defined as the set of all wrenches that a legged robot can realize given its actuation capabilities and the friction constraints. Results are reported where, thanks to efficient computational geometry algorithms and to appropriate approximations, the FWP is employed for a one-step receding horizon optimization of center of mass trajectory and phase durations given a predefined step sequence on rough terrains. For the sake of reachable workspace augmentation, I then decided to trade off the generality of the FWP formulation for a suboptimal scenario in which a quasi-static motion is assumed. This led to the definition of the, so called, local/instantaneous actuation region and of the global actuation/feasible region. They both can be seen as different variants of 2D linear subspaces orthogonal to gravity where the robot is guaranteed to place its own center of mass while being able to carry its own body weight given its actuation capabilities. These areas can be intersected with the well known frictional support region, resulting in a 2D linear feasible region, thus providing an intuitive tool that enables the concurrent online optimization of actuation consistent CoM trajectories and target foothold locations on rough terrains