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A virtual environment for the modelling, simulation and manufacturing of orthopaedic devices
This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.The objective of this work is to investigate whether the game physics based
modelling is accurate enough to be used in modelling the motion of the human body,
in particular musculoskeletal motion. Hitherto, the implementation of game physics
in the medical field focused only on anatomical representation for education and
training purposes. Introducing gaming platforms and physics engines into
orthopaedics applications will help to overcome several difficulties encountered in
the modelling of articular joints. Implementing a physics engine (PhysX), which is mainly designed for video games, handles intensive computations in optimized ways
at an interactive speed. In this study, the capabilities of the physics engine (PhysX)
and gaming platform for modelling and simulating articular joints are evaluated.
First, a preliminary validation is carried out for mechanical systems with analytical
solutions, before constructing the musculoskeletal model to evaluate the consistency of gaming platforms. The developed musculoskeletal model deals with the human joint as an unconstrained system with 6 DOF which is not available with other joint modeller. The model articulation is driven by contact surfaces and the stiffness of surrounding tissues. A number of contributions, such as contact modelling and
muscle wrapping, have been made in this research to overcome some existing
challenges in joint modelling. Using muscle segmentation, the proposed technique
effectively handles the problem of muscle wrapping, a major concern for many; thus
the shortest path and line of action are no longer problematic. Collision behaviour
has also shown a stable response for colliding as well as resting objects, provided that it is based on the principles of surface properties and the conservation of linear and angular momentums. The precision of collision detection and response are within an acceptable tolerance controllable by varying the mesh density. An image based analysis system is developed in this thesis, mainly in order to validate the
proposed physics based modelling solution. This minimally invasive method is based
on the analysis of marker positions located at bony positions with minimal skin
movement. The image based system overcomes several challenges associated with
the currently existing methods, such as inaccuracy, complication, impracticability
and cost. The analysis part of this research has considered the elbow joint as a case
study to investigate and validate the proposed physics based model. Beside the
interactive 3D simulation, the obtained results are validated by comparing them with
the image based system developed within the current research to investigate joint
kinematics and laxity and also with published material, MJM and results from
experiments performed at the Brunel Orthopaedic Research and Learning Centre.
The proposed modelling shows the advantageous speed, reliability and flexibility of the proposed model. It is shown that the gaming platform and physics engine provide a viable solution to human musculoskeletal modelling. Finally, this thesis considers an extended implementation of the proposed platform for testing and assessing the design of custom-made implants, to enhance joint performance. The developed simulation software is expected to give indicative results as well as testing different types of prosthetic implant. Design parameterization and sensitivity analysis for geometrical features are discussed. Thus, an integrated environment is proposed to link the real-time simulation software with a manufacturing environment so as to assist the production of patient specific implants by rapid manufacturing
FPGA-based High-Performance Collision Detection: An Enabling Technique for Image-Guided Robotic Surgery
Collision detection, which refers to the computational problem of finding the relative placement or con-figuration of two or more objects, is an essential component of many applications in computer graphics and robotics. In image-guided robotic surgery, real-time collision detection is critical for preserving healthy anatomical structures during the surgical procedure. However, the computational complexity of the problem usually results in algorithms that operate at low speed. In this paper, we present a fast and accurate algorithm for collision detection between Oriented-Bounding-Boxes (OBBs) that is suitable for real-time implementation. Our proposed Sweep and Prune algorithm can perform a preliminary filtering to reduce the number of objects that need to be tested by the classical Separating Axis Test algorithm, while the OBB pairs of interest are preserved. These OBB pairs are re-checked by the Separating Axis Test algorithm to obtain accurate overlapping status between them. To accelerate the execution, our Sweep and Prune algorithm is tailor-made for the proposed method. Meanwhile, a high performance scalable hardware architecture is proposed by analyzing the intrinsic parallelism of our algorithm, and is implemented on FPGA platform. Results show that our hardware design on the FPGA platform can achieve around 8X higher running speed than the software design on a CPU platform. As a result, the proposed algorithm can achieve a collision frame rate of 1 KHz, and fulfill the requirement for the medical surgery scenario of Robot Assisted Laparoscopy.published_or_final_versio
New geometric algorithms and data structures for collision detection of dynamically deforming objects
Any virtual environment that supports interactions between virtual objects and/or a user and objects,
needs a collision detection system to handle all interactions in a physically correct or plausible way. A
collision detection system is needed to determine if objects are in contact or interpenetrates. These
interpenetrations are resolved by a collision handling system. Because of the fact, that in nearly all
simulations objects can interact with each other, collision detection is a fundamental technology, that
is needed in all these simulations, like physically based simulation, robotic path and motion planning,
virtual prototyping, and many more. Most virtual environments aim to represent the real-world as
realistic as possible and therefore, virtual environments getting more and more complex. Furthermore,
all models in a virtual environment should interact like real objects do, if forces are applied to the
objects. Nearly all real-world objects will deform or break down in its individual parts if forces are
acted upon the objects. Thus deformable objects are becoming more and more common in virtual
environments, which want to be as realistic as possible and thus, will present new challenges to the
collision detection system. The necessary collision detection computations can be very complex and this
has the effect, that the collision detection process is the performance bottleneck in most simulations.
Most rigid body collision detection approaches use a BVH as acceleration data structure. This
technique is perfectly suitable if the object does not change its shape. For a soft body an update step
is necessary to ensure that the underlying acceleration data structure is still valid after performing a
simulation step. This update step can be very time consuming, is often hard to implement and in most
cases will produce a degenerated BVH after some simulation steps, if the objects generally deform.
Therefore, the here presented collision detection approach works entirely without an acceleration data
structure and supports rigid and soft bodies. Furthermore, we can compute inter-object and intraobject
collisions of rigid and deformable objects consisting of many tens of thousands of triangles in a
few milliseconds. To realize this, a subdivision of the scene into parts using a fuzzy clustering approach
is applied. Based on that all further steps for each cluster can be performed in parallel and if desired,
distributed to different GPUs. Tests have been performed to judge the performance of our approach
against other state-of-the-art collision detection algorithms. Additionally, we integrated our approach
into Bullet, a commonly used physics engine, to evaluate our algorithm.
In order to make a fair comparison of different rigid body collision detection algorithms, we propose
a new collision detection Benchmarking Suite. Our Benchmarking Suite can evaluate both the performance
as well as the quality of the collision response. Therefore, the Benchmarking Suite is subdivided
into a Performance Benchmark and a Quality Benchmark. This approach needs to be extended to
support soft body collision detection algorithms in the future.Jede virtuelle Umgebung, welche eine Interaktion zwischen den virtuellen Objekten in der Szene
zulässt und/oder zwischen einem Benutzer und den Objekten, benötigt für eine korrekte Behandlung der
Interaktionen eine Kollisionsdetektion. Nur dank der Kollisionsdetektion können Berührungen zwischen
Objekten erkannt und mittels der Kollisionsbehandlung aufgelöst werden. Dies ist der Grund für die weite
Verbreitung der Kollisionsdetektion in die verschiedensten Fachbereiche, wie der physikalisch basierten
Simulation, der Pfadplanung in der Robotik, dem virtuellen Prototyping und vielen weiteren. Auf Grund
des Bestrebens, die reale Umgebung in der virtuellen Welt so realistisch wie möglich nachzubilden,
steigt die Komplexität der Szenen stetig. Fortwährend steigen die Anforderungen an die Objekte, sich
realistisch zu verhalten, sollten Kräfte auf die einzelnen Objekte ausgeübt werden. Die meisten Objekte,
die uns in unserer realen Welt umgeben, ändern ihre Form oder zerbrechen in ihre Einzelteile, wenn
Kräfte auf sie einwirken. Daher kommen in realitätsnahen, virtuellen Umgebungen immer häufiger
deformierbare Objekte zum Einsatz, was neue Herausforderungen an die Kollisionsdetektion stellt. Die
hierfür Notwendigen, teils komplexen Berechnungen, führen dazu, dass die Kollisionsdetektion häufig
der Performance-Bottleneck in der jeweiligen Simulation darstellt.
Die meisten Kollisionsdetektionen für starre Körper benutzen eine Hüllkörperhierarchie als Beschleunigungsdatenstruktur.
Diese Technik ist hervorragend geeignet, solange sich die Form des Objektes
nicht verändert. Im Fall von deformierbaren Objekten ist eine Aktualisierung der Datenstruktur nach
jedem Schritt der Simulation notwendig, damit diese weiterhin gültig ist. Dieser Aktualisierungsschritt
kann, je nach Hierarchie, sehr zeitaufwendig sein, ist in den meisten Fällen schwer zu implementieren
und generiert nach vielen Schritten der Simulation häufig eine entartete Hüllkörperhierarchie, sollte
sich das Objekt sehr stark verformen. Um dies zu vermeiden, verzichtet unsere Kollisionsdetektion vollständig
auf eine Beschleunigungsdatenstruktur und unterstützt sowohl rigide, wie auch deformierbare
Körper. Zugleich können wir Selbstkollisionen und Kollisionen zwischen starren und/oder deformierbaren
Objekten, bestehend aus vielen Zehntausenden Dreiecken, innerhalb von wenigen Millisekunden
berechnen. Um dies zu realisieren, unterteilen wir die gesamte Szene in einzelne Bereiche mittels eines
Fuzzy Clustering-Verfahrens. Dies ermöglicht es, dass alle Cluster unabhängig bearbeitet werden und
falls gewünscht, die Berechnungen für die einzelnen Cluster auf verschiedene Grafikkarten verteilt werden
können. Um die Leistungsfähigkeit unseres Ansatzes vergleichen zu können, haben wir diesen gegen
aktuelle Verfahren für die Kollisionsdetektion antreten lassen. Weiterhin haben wir unser Verfahren in
die Physik-Engine Bullet integriert, um das Verhalten in dynamischen Situationen zu evaluieren.
Um unterschiedliche Kollisionsdetektionsalgorithmen für starre Körper korrekt und objektiv miteinander
vergleichen zu können, haben wir eine Benchmarking-Suite entwickelt. Unsere Benchmarking-
Suite kann sowohl die Geschwindigkeit, für die Bestimmung, ob zwei Objekte sich durchdringen, wie
auch die Qualität der berechneten Kräfte miteinander vergleichen. Hierfür ist die Benchmarking-Suite
in den Performance Benchmark und den Quality Benchmark unterteilt worden. In der Zukunft wird
diese Benchmarking-Suite dahingehend erweitert, dass auch Kollisionsdetektionsalgorithmen für deformierbare
Objekte unterstützt werden
A Broad Phase Collision Detection Algorithm Adapted to Multi-cores Architectures
International audienceRecent years have seen the impressive evolution of graphics hardware and processors architecture from single core to multi and many-core architectures. Confronted to this evolution, new trends in collision detection optimisation consist in proposing a solution that maps on the runtime architecture. We present, in this paper, two contributions in the field of collision detection in large-scale environments. We present a first way to parallelise, on a multi-core architecture, the initial step of the collision detection pipeline: the broad-phase. Then, we describe a new formalism of the collision detection pipeline that takes into account runtime architecture. The well-known broadphase algorithm used is the ”Sweep and Prune” and it has been adapted to a multi-threading use. To handle one or more thread per core, critical writing sections and threads idling must be minimised. Our model is able to work on a n-core architecture reducing computation time to detect collision between 3D objects in a large-scale environment
New Geometric Data Structures for Collision Detection
We present new geometric data structures for collision detection and more, including: Inner Sphere Trees - the first data structure to compute the peneration volume efficiently. Protosphere - an new algorithm to compute space filling sphere packings for arbitrary objects. Kinetic AABBs - a bounding volume hierarchy that is optimal in the number of updates when the objects deform. Kinetic Separation-List - an algorithm that is able to perform continuous collision detection for complex deformable objects in real-time. Moreover, we present applications of these new approaches to hand animation, real-time collision avoidance in dynamic environments for robots and haptic rendering, including a user study that exploits the influence of the degrees of freedom in complex haptic interactions. Last but not least, we present a new benchmarking suite for both, peformance and quality benchmarks, and a theoretic analysis of the running-time of bounding volume-based collision detection algorithms
Interactive ray tracing of massive and deformable models
Ray tracing is a fundamental algorithm used for many applications such as computer graphics, geometric simulation, collision detection and line-of-sight computation. Even though the performance of ray tracing algorithms scales with the model complexity, the high memory requirements and the use of static hierarchical structures pose problems with massive models and dynamic data-sets. We present several approaches to address these problems based on new acceleration structures and traversal algorithms. We introduce a compact representation for storing the model and hierarchy while ray tracing triangle meshes that can reduce the memory footprint by up to 80%, while maintaining high performance. As a result, can ray trace massive models with hundreds of millions of triangles on workstations with a few gigabytes of memory. We also show how to use bounding volume hierarchies for ray tracing complex models with interactive performance. In order to handle dynamic scenes, we use refitting algorithms and also present highly-parallel GPU-based algorithms to reconstruct the hierarchies. In practice, our method can construct hierarchies for models with hundreds of thousands of triangles at interactive speeds. Finally, we demonstrate several applications that are enabled by these algorithms. Using deformable BVH and fast data parallel techniques, we introduce a geometric sound propagation algorithm that can run on complex deformable scenes interactively and orders of magnitude faster than comparable previous approaches. In addition, we also use these hierarchical algorithms for fast collision detection between deformable models and GPU rendering of shadows on massive models by employing our compact representations for hybrid ray tracing and rasterization
Haptic Interaction with 3D oriented point clouds on the GPU
Real-time point-based rendering and interaction with virtual objects is gaining popularity
and importance as di�erent haptic devices and technologies increasingly provide the basis
for realistic interaction. Haptic Interaction is being used for a wide range of applications
such as medical training, remote robot operators, tactile displays and video games. Virtual
object visualization and interaction using haptic devices is the main focus; this process
involves several steps such as: Data Acquisition, Graphic Rendering, Haptic Interaction
and Data Modi�cation. This work presents a framework for Haptic Interaction using the
GPU as a hardware accelerator, and includes an approach for enabling the modi�cation
of data during interaction. The results demonstrate the limits and capabilities of these
techniques in the context of volume rendering for haptic applications. Also, the use
of dynamic parallelism as a technique to scale the number of threads needed from the
accelerator according to the interaction requirements is studied allowing the editing of
data sets of up to one million points at interactive haptic frame rates
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