Real-time performance and accuracy are two most challenging requirements in virtual surgery training.These difficulties limit the promotion of advanced models in virtual surgery,including many geometric and physical models.This paper proposes a physical model of virtual soft tissue,which is a twist model based on the Kriging interpolation and membrane analogy.The proposed model can quickly locate spatial position through Kriging interpolation method and accurately compute the force change on the soft tissue through membrane analogy method.The virtual surgery simulation system is built with a PHANTOM OMNI haptic interaction device to simulate the torsion of virtual stomach and arm,and further verifies the real-time performance and simulation accuracy of the proposed model.The experimental results show that the proposed soft tissue model has high speed and accuracy,realistic deformation,and reliable haptic feedback.
In order to solve the problem that the existing meshless models are of high computational complexity and are difficult to express the biomechanical characteristics of real soft tissue, a local high-resolution deformation model of soft tissue based on element-free Galerkin method is proposed. The proposed model applies an element-free Galerkin method to establish the model, and integrates Kelvin viscoelastic model and adjustment function to simulate nonlinear viscoelasticity of soft tissue. Meanwhile, a local high-resolution algorithm is applied to sample and render the deformed region of the model to reduce the computational complexity. To verify the effectiveness of the model,liver and brain tumor deformation simulation experiments are carried out. The experimental results show that compared with the existing meshless models, the proposed model well reflects the biomechanical characteristics of soft tissue, and is of high authenticity, which can provide better visual feedback to users while reducing computational cost.
The modelling and simulation of deformable objects is a challenging topic in the field of haptic rendering between human and virtual environment.In this paper,a novel and efficient layered rhombus-chain-connected haptic deformation model based on physics is proposed for an excellent haptic rendering.During the modelling,the accumulation of relative displacements in every chain structure unit in each layer is equal to the deformation on the virtual object surface,and the resultant force of corresponding springs is equivalent to the external force.The layered rhombus-chain-connected model is convenient and fast to calculate,and can satisfy real-time requirement due to its simple nature.Simulation experiments in virtual human liver based on the proposed model are conducted,and the results demonstrate that our model provides stable and realistic haptic feeling in real time.Meanwhile,the display result is vivid.
To improve the accuracy and interactivity of soft tissue delormatlon simulation, a new plate spring model based on physics is proposed. The model is parameterized and thus can be adapted to simulate different organs. Different soft tissues are modeled by changing the width, number of pieces, thickness, and length of a single plate spring. In this paper, the structural design, calcula- tion of soft tissue deformation and real-time feedback operations of our system are also introduced. To evaluate the feasibility of the system and validate the model, an experimental system of haptic in- teraction, in which users can use virtual hands to pull virtual brain tissues, is built using PHANTOM OMNI devices. Experimental results show that the proposed system is stable, accurate and promising for modeling instantaneous soft tissue deformation.
Abnormal driving behavior identification( ADBI) has become a research hotspot because of its significance in driver assistance systems. However,current methods still have some limitations in terms of accuracy and reliability under severe traffic scenes. This paper proposes a new ADBI method based on direction and position offsets,where a two-factor identification strategy is proposed to improve the accuracy and reliability of ADBI. Self-adaptive edge detection based on Sobel operator is used to extract edge information of lanes. In order to enhance the efficiency and reliability of lane detection,an improved lane detection algorithm is proposed,where a Hough transform based on local search scope is employed to quickly detect the lane,and a validation scheme based on priori information is proposed to further verify the detected lane. Experimental results under various complex road conditions demonstrate the validity of the proposed ADBI.
