Stable Real-Time Surgical Cutting Simulation of Deformable Objects Embedded with Arbitrary Triangular Meshes

Surgical simulators need to simulate deformation and cutting of deformable objects. Adaptive octree mesh based cutting methods embed the deformable objects into octree meshes that are recursively refined near the cutting tool trajectory. Deformation is only applied to the octree meshes; thus the deformation instability problem caused by degenerated elements is avoided. Biological tissues and organs usually contain complex internal structures that are ignored by previous work. In this paper the deformable objects are modeled as voxels connected by links and embedded inside adaptive octree meshes. Links swept by the cutting tool are disconnected and object surface meshes are reconstructed from disconnected links. Two novel methods for embedding triangular meshes as internal structures are proposed. The surface mesh embedding method is applicable to arbitrary triangular meshes, but these meshes have no physical properties. The material sub-region embedding method associates the interiors enclosed by the triangular meshes with physical properties, but requires that these meshes are watertight, and have no self-intersections, and their smallest features are larger than a voxel. Some local features are constructed in a pre-calculation stage to increase simulation performance. Simulation tests show that our methods can cut embedded structures in a way consistent with the cutting of the deformable objects. Cut fragments can also deform correctly along with the deformable objects.

BADF:Bounding Volume Hierarchies Centric Adaptive Distance Field Computation for Deformable Objects on GPUs

We present a novel algorithm BADF(Bounding Volume Hierarchy Based Adaptive Distance Fields)for accelerating the construction of ADFs(adaptive distance fields)of rigid and deformable models on graphics processing units.Our approach is based on constructing a bounding volume hierarchy(BVH)and we use that hierarchy to generate an octree-based ADF.We exploit the coherence between successive frames and sort the grid points of the octree to accelerate the computation.Our approach is applicable to rigid and deformable models.Our GPU-based(graphics processing unit based)algorithm is about 20x--50x faster than current mainstream central processing unit based algorithms.Our BADF algorithm can construct the distance fields for deformable models with 60k triangles at interactive rates on an NVIDIA GTX GeForce 1060.Moreover,we observe 3x speedup over prior GPU-based ADF algorithms.

A graph theory model using human nature structure

A graph theory model of the human nature structure( GMH) for machine vision and image/graphics processing is described in this paper. Independent from the motion and deformation of contours,the human nature structure( HNS) embodies the most basic movement characteristics of the body. The human body can be divided into basic units like head,torso,and limbs. Using these basic units,a graph theory model for the HNS can be constructed. GMH provides a basic model for human posture processing,and the outline in the perspective projection plane is the body contour of an image. In addition,the GMH can be applied to articulated motion and deformable objects,e. g.,in the design and analysis of body posture,by modifying mapping parameters of the GMH.

Real-time Volume Preserving Constraints for Volumetric Model on GPU

This paper presents a parallel method for simulating real-time 3D deformable objects using the volume preservation mass-spring system method on tetrahedron meshes.In general,the conventional mass-spring system is manipulated as a force-driven method because it is fast,simple to implement,and the parameters can be controlled.However,the springs in traditional mass-spring system can be excessively elongated which cause severe stability and robustness issues that lead to shape restoring,simulation blow-up,and huge volume loss of the deformable object.In addition,traditional method that uses a serial process of the central processing unit(CPU)to solve the system in every frame cannot handle the complex structure of deformable object in real-time.Therefore,the first order implicit constraint enforcement for a mass-spring model is utilized to achieve accurate visual realism of deformable objects with tough constraint error.In this paper,we applied the distance constraint and volume conservation constraints for each tetrahedron element to improve the stability of deformable object simulation using the mass-spring system and behave the same as its real-world counterparts.To reduce the computational complexity while ensuring stable simulation,we applied a method that utilizes OpenGL compute shader,a part of OpenGL Shading Language(GLSL)that executes on the graphic processing unit(GPU)to solve the numerical problems effectively.We applied the proposed methods to experimental volumetric models,and volume percentages of all objects are compared.The average volume percentages of all models during the simulation using the mass-spring system,distance constraint,and the volume constraint method were 68.21%,89.64%,and 98.70%,respectively.The proposed approaches are successfully applied to improve the stability of mass-spring system and the performance comparison from our experimental tests also shows that the GPU-based method is faster than CPU-based implementation for all cases.

Surface Deformation with Multi-constraints Based on the Minimum Energy

A method for deformation of 3D point clouds models was proposed with multi-constraints including arc-length constraints and multi-points position constraints. The energy function was built for the polyline which had been converted from the curve. Based on the minimum energy curve method, the curve on the mesh was deformed. The test results show that the proposed method has good performance. Compared with the other method,shape preserving of the curve is better. Finally,this method is used for the deformation of the 3D mannequin model. Circumference changes of the mannequin model can be reflected by the arc-length change in the size of the cross section.

Measurement of out-of-plane deformation of curved objects with digital speckle pattern interferometry

Digital speckle pattern interferometry （DSPI） is a high-precision deformation t technique for planar objects. However, for curved objects, the three-dimensional （3D） shape information is needed in order to obtain correct deformation measurement in DSPI. Thus, combined shape and deformation measurement techniques of DSPI have been proposed. However, the current techniques are either complex in setup or complicated in operation. Furthermore, the operations of some techniques are too slow for real-time measurement. In this work, we propose a DSPI technique for both 3D shape and out-of-plane deformation measurement. Compared with current techniques, the proposed technique is simple in both setup and operation and is capable of fast deformation measurement. Theoretical analysis and experiments are performed. For a cylinder surface with an arch height of 9 mm, the error of out-of-plane deformation measurement is less than 0.15 μm. The effectiveness of the proposed scheme is verified.

An online impedance adaptation controller for decoding skill intelligence

Variable Impedance control allows robots and humans to safely and efficiently interact with unknown external environments.This tutorial introduces online impedance adaptation control(OIAC)for variable compliant joint motions in a range of control tasks:rapid(<1 s)movement control(i.e.,whipping to hit),arm and finger impedance quantification,multifunctional exoskeleton control,and robot-inspired human arm control hypothesis.The OIAC has been introduced as a feedback control,which can be integrated into a feedforward control,e.g.,learned by data-driven methods.This integration facilitates the understanding of human and robot arm control,closing a research loop between biomechanics and robotics.It shows not only a research way from biomechanics to robotics,but also another reserved one.This tutorial aims at presenting research examples and Python codes for advancing the understanding of variable impedance adaptation in human and robot motor control.It contributes to the state-of-the-art by providing an online impedance adaptation controller for wearable robots(i.e.,exoskeletons)which can be used in robotic and biomechanical applications.