Scalable partitioning for parallel position based dynamics

We introduce a practical partitioning technique designed for parallelizing Position Based Dynamics, and exploiting the ubiquitous multi-core processors present in current commodity GPUs. The input is a set of particles whose dynamics is influenced by spatial constraints. In the initialization phase, we build a graph in which each node corresponds to a constraint and two constraints are connected by an edge if they influence at least one common particle. We introduce a novel greedy algorithm for inserting additional constraints (phantoms) in the graph such that the resulting topology is q-colourable, where ˆ qˆ ≥ 2 is an arbitrary number. We color the graph, and the constraints with the same color are assigned to the same partition. Then, the set of constraints belonging to each partition is solved in parallel during the animation phase. We demonstrate this by using our partitioning technique; the performance hit caused by the GPU kernel calls is significantly decreased, leaving unaffected the visual quality, robustness and speed of serial position based dynamics

Smarticles: A Method for Identifying and Correcting Instability and Error Caused by Explicit Integration Techniques in Physically Based Simulations

Using an explicit integration method in physically based animations has many advantages including conceptual and computational simplicity, however, it re- quires small time steps to ensure low numerical instability. Simulations with large numbers of individually interacting components such as cloth, hair, and fluid models, are limited by the sections of particles most susceptible to error. This results in the need for smaller time steps than required for the majority of the system. These sections can be diverse and dynamic, quickly changing in size and location based on forces in the system. Identifying and handling these trou- blesome sections could allow for a larger time step to be selected, while preventing a breakdown in the simulation. This thesis presents Smarticles (smart particles), a method of individually de- tecting particles exhibiting signs of instability and stabilizing them with minimal adverse effects to visual accuracy. As a result, higher levels of error introduced from large time steps can be tolerated with minimal overhead. Two separate approaches to Smarticles were implemented. They attempt to find oscillating particles by analyzing a particle’s (1) past behavior and (2) behavior with re- spect to its neighbors along a strand. Both versions of Smarticles attempt to correct unstable particles using velocity dampening. Smarticles was applied to a two dimensional hair simulation modeled as a continuum using smooth particle hydrodynamic. Hair strands are formed by linking particles together using one of two methods: position based dynamics or mass-spring forces. Both versions of Smarticles, as well as a control of normal particles, were directly compared and evaluated based on stability and visual fluidity. Hair particles were exposed to various forms of external forces under increasing time step lengths. Testing showed that both versions of Smarticles working together allowed an average increase of 18.62% in the time step length for hair linked with position based dynamics. In addition, Smarticles was able to significantly reduce visible instability at even larger time steps. While these results suggest Smarticles is successful, the method used to correct particle instability may jeopardize other important aspects of the simulation. A more accurate correction method would likely need to be developed to make Smarticles an advantageous method

Position-based modeling of lesion displacement in Ultrasound-guided breast biopsy

International audiencePurpose Although ultrasound (US) images represent the most popular modality for guiding breast biopsy, malignant regions are often missed by sonography, thus preventing accurate lesion localization which is essential for a successful procedure. Biomechanical models can support the localization of suspicious areas identified on a pre-operative image during US scanning since they are able to account for anatomical deformations resulting from US probe pressure. We propose a deformation model which relies on position-based dynamics (PBD) approach to predict the displacement of internal targets induced by probe interaction during US acquisition. Methods The PBD implementation available in NVIDIA FleX is exploited to create an anatomical model capable of deforming online. Simulation parameters are initialized on a calibration phantom under different levels of probe-induced deformations, then they are fine-tuned by minimizing the localization error of a US-visible landmark of a realistic breast phantom. The updated model is used to estimate the displacement of other internal lesions due to probe-tissue interaction. Results The localization error obtained when applying the PBD model remains below 11 mm for all the tumors even for input displacements in the order of 30 mm. This proposed method obtains results aligned with FE models with faster computational performance, suitable for real-time applications. In addition, it outperforms rigid model used to track lesion position in US-guided breast biopsies, at least halving the localization error for all the displacement ranges considered. 2 Eleonora Tagliabue et al. Conclusions Position-based dynamics approach has proved to be successful in modeling breast tissue deformations during US acquisition. Its stability, accuracy and real-time performance make such model suitable for tracking lesions displacement during US-guided breast biopsy

Visuohaptic Simulation of a Borescope for Aircraft Engine Inspection

Consisting of a long, fiber optic probe containing a small CCD camera controlled by hand-held articulation interface, a video borescope is used for remote visual inspection of hard to reach components in an aircraft. The knowledge and psychomotor skills, specifically the hand-eye coordination, required for effective inspection are hard to acquire through limited exposure to the borescope in aviation maintenance schools. Inexperienced aircraft maintenance technicians gain proficiency through repeated hands-on learning in the workplace along a steep learning curve while transitioning from the classroom to the workforce. Using an iterative process combined with focused user evaluations, this dissertation details the design, implementation and evaluation of a novel visuohaptic simulator for training novice aircraft maintenance technicians in the task of engine inspection using a borescope. First, we describe the development of the visual components of the simulator, along with the acquisition and modeling of a representative model of a {PT-6} aircraft engine. Subjective assessments with both expert and novice aircraft maintenance engineers evaluated the visual realism and the control interfaces of the simulator. In addition to visual feedback, probe contact feedback is provided through a specially designed custom haptic interface that simulates tip contact forces as the virtual probe intersects with the {3D} model surfaces of the engine. Compared to other haptic interfaces, the custom design is unique in that it is inexpensive and uses a real borescope probe to simulate camera insertion and withdrawal. User evaluation of this simulator with probe tip feedback suggested a trend of improved performance with haptic feedback. Next, we describe the development of a physically-based camera model for improved behavioral realism of the simulator. Unlike a point-based camera, the enhanced camera model simulates the interaction of the borescope probe, including multiple points of contact along the length of the probe. We present visual comparisons of a real probe\u27s motion with the simulated probe model and develop a simple algorithm for computing the resultant contact forces. User evaluation comparing our custom haptic device with two commonly available haptic devices, the Phantom Omni and the Novint Falcon, suggests that the improved camera model as well as probe contact feedback with the 3D engine model plays a significant role in the overall engine inspection process. Finally, we present results from a skill transfer study comparing classroom-only instruction with both simulator and hands-on training. Students trained using the simulator and the video borescope completed engine inspection using the real video borescope significantly faster than students who received classroom-only training. The speed improvements can be attributed to reduced borescope probe maneuvering time within the engine and improved psychomotor skills due to training. Given the usual constraints of limited time and resources, simulator training may provide beneficial skills needed by novice aircraft maintenance technicians to augment classroom instruction, resulting in a faster transition into the aviation maintenance workforce

Patient-specific simulation for autonomous surgery

An Autonomous Robotic Surgical System (ARSS) has to interact with the complex anatomical environment, which is deforming and whose properties are often uncertain. Within this context, an ARSS can benefit from the availability of patient-specific simulation of the anatomy. For example, simulation can provide a safe and controlled environment for the design, test and validation of the autonomous capabilities. Moreover, it can be used to generate large amounts of patient-specific data that can be exploited to learn models and/or tasks. The aim of this Thesis is to investigate the different ways in which simulation can support an ARSS and to propose solutions to favor its employability in robotic surgery. We first address all the phases needed to create such a simulation, from model choice in the pre-operative phase based on the available knowledge to its intra-operative update to compensate for inaccurate parametrization. We propose to rely on deep neural networks trained with synthetic data both to generate a patient-specific model and to design a strategy to update model parametrization starting directly from intra-operative sensor data. Afterwards, we test how simulation can assist the ARSS, both for task learning and during task execution. We show that simulation can be used to efficiently train approaches that require multiple interactions with the environment, compensating for the riskiness to acquire data from real surgical robotic systems. Finally, we propose a modular framework for autonomous surgery that includes deliberative functions to handle real anatomical environments with uncertain parameters. The integration of a personalized simulation proves fundamental both for optimal task planning and to enhance and monitor real execution. The contributions presented in this Thesis have the potential to introduce significant step changes in the development and actual performance of autonomous robotic surgical systems, making them closer to applicability to real clinical conditions

Development of Techniques for Modeling the Static Buckling of Euler Beam and Dynamic Response of Kirchhoff Rods: Application to Surgical Simulation and Training

In this dissertation, we present novel schemes for a static simulation of a buckled Euler beam with curve channel constraints in two dimensional space and simulation of the dynamic response of a soft Kirchhoff rod in three dimension space at real time rate. The aim of this model is to provide a robust and fast means for simulating endoscopes and surgical threads for training and surgical simulation purposes. Finding a static configuration of a buckled cantilever elastic beam constrained in a curved solid channel subject to end forces is a simple model of endoscopy and it is posed as the minimization of an energy functional. We solve it by a novel technique, a variant of a dynamic programming approach called the Viterbi algorithm. The core idea of this approach is to discretize the variables describing the potential energy and to construct a set of admissible configurations of the beam. The Viterbi algorithm is then employed to search through the set of possible beam configurations and locate the one with the minimum potential energy in a very computationally efficient way. The new approach does not require any gradient computations and could be considered as a direct search method, and thus can be guaranteed to find the global minimum potential energy. Also the constraints can be automatically satisfied by constructing the proper set of all the possible configurations. The approach can also be used to find feasible starting configurations associated with conventional minimizing algorithms. We also discuss a novel scheme based on discrete variational integrators to study the dynamics of an inextensible thin Kirchhoff rod which is a model for a surgical thread. The benefits of such approach are that it is a very efficient scheme that guarantees conservation of momentum and energy over very long times so that a real time simulator can be operated over long periods of time. In addition, we report on an innovative technique to capture the inextensibility as well as the internal dissipation of the rod efficiently. Finally, a new collision avoidance scheme based on a continuous penalty force is employed to simulate the interaction of the rod with the surrounding medium. The simulations performed capture the formation of plectoneme, i.e. a loop of helices twisted together. Lastly, the scheme is employed to simulate the tying of a square knot. This model can be used to simulate surgical threads at real time rate

A robust method for real-time thread simulation

In this paper, we present a physically based model for real-time simulation of thread dynamics. Our model captures all the relevant aspects of the physics of the thread, including quasi-zero elasticity, bending, torsion and self-collision, and it provides output forces for the haptic feedback. The physical properties are modeled in terms of constraints that are iteratively satisfied while the numerical integration is carried out through a Verlet scheme. This approach leads to an unconditionally stable, controllable and computationally light simulation [Müller et al. 2007]. Our results demonstrate the effectiveness of our model, showing the interaction of the thread with other objects in real time and the creation of complex knots. © 2007 ACM