scholarly journals Real Time Estimator to Perform Targeted Biopsies With a Free-Wrist Robot Despite Large Deformations of the Insertion Orifice

2021 ◽  
Vol 8 ◽  
Author(s):  
Rémi Chalard ◽  
Afshin Fazel ◽  
Marie-Aude Vitrani
Keyword(s):  
Real Time ◽  
Large Deformations ◽  
Jacobian Matrix ◽  
Interaction Matrix ◽  
Surgical Instrument ◽  
Keyhole Surgery ◽  
Broyden Method ◽  
Pointing Task ◽  
Tissue Deformations ◽  
Targeted Biopsies

In the context of keyhole surgery, and more particularly of uterine biopsy, the fine automatic movements of a surgical instrument held by a robot with 3 active DOF’s require an exact knowledge of the point of rotation of the instrument. However, this center of rotation is not fixed and moves during an examination. This paper deals with a new method of detecting and updating the interaction matrix linking the movements of the robot with the surgical instrument. This is based on the method of updating the Jacobian matrix which is named the “Broyden method”. It is able to take into account body tissue deformations in real time in order to improve the pointing task for automatic movements of a surgical instrument in an unknown environment.

Real-Time Flow Optimization of Hydraulic Manipulator with One Degree of Redundancy Considering Joint Limit Constraint

2021 ◽  
Author(s):  
Linan Li ◽  
Min Cheng ◽  
Ruqi Ding ◽  
Junhui Zhang ◽  
Bing Xu
Keyword(s):  
Real Time ◽  
Projection Method ◽  
Jacobian Matrix ◽  
Gradient Projection ◽  
Redundancy Resolution ◽  
Flow Optimization ◽  
Hydraulic Manipulators ◽  
Time Flow ◽  
Hydraulic Manipulator ◽  
Joint Limit

Abstract Due to the complexity in unstructured environments (e.g., rescue response and forestry logging), more hydraulic manipulators are equipped with one redundant joint to improve their motion flexibility. In addition to considering joint limit constraint and maneuverability optimization like electrically driven manipulators, hydraulic manipulators can optimize flow consumption consider flow optimization aiming at energy saving and flow anti-saturation for redundancy resolution, since multiple joints are supplied by one pump. Therefore, this paper proposes a redundancy resolution method combining the gradient projection method with a weighted Jacobian matrix (GPM-WJM) for real-time flow optimization of the hydraulic manipulator with one degree of redundancy considering joint limit constraint. Its solution consists of two parts: a special solution (the weighted least-norm solution) and a general solution (the projection of the optimization index in the null space of the weighted task Jacobian matrix). Simulations are carried out to verify its effectiveness. The simulation result shows that GPM-WJM can meet the constraints of joint limit without affecting the tool center point (TCP) trajectory and utilize the remaining redundancy to optimize the flow consumption and manipulability in real-time, which can reduce average system flow by 10.45%. Compared with the gradient projection method (GPM) for flow optimization, GPM-WJM can reduce the maximum acceleration when avoiding the joint limits by 80% at the cost of slightly weakening the flow optimization effect, which is beneficial to improve the accuracy of the manipulator in practice.

Real Time Techniques for Nonlinear Tissue Deformation in Surgical Simulation

2007 ◽  
Author(s):  
Suvranu De ◽  
Yi-Je Lim
Keyword(s):  
Finite Element ◽  
Real Time ◽  
Surgical Simulation ◽  
Computational Technique ◽  
Finite Element Models ◽  
Geometrically Nonlinear ◽  
Time Performance ◽  
Surgical Tool ◽  
Surgical Simulations ◽  
Tissue Deformations

The requirement of real time performance, crucial to multimodal surgical simulations, imposes severe demands in terms of computational efficiency. A physics-based meshfree computational technique known as the Point-Associated Finite Field (PAFF) approach has been developed to circumvent many outstanding problems associated with traditional mesh-based computational schemes and has been applied in this paper to the modeling of geometrically nonlinear tissue deformations. The technique is based on a novel combination of multiresolution approach coupled with a fast reanalysis scheme in which the response predicted by an underlying linear PAFF model is enhanced in the local neighborhood of the surgical tool-tip by a nonlinear model. We present performance comparisons of PAFF with traditional finite element models.

scholarly journals An Efficient Approach For the Nodal Water Demand Estimation in Large-Scale Water Distribution Systems

2021 ◽  
Author(s):  
Shipeng Chu ◽  
Tuqiao Zhang ◽  
Xinhong Zhou ◽  
Tingchao Yu ◽  
Yu Shao
Keyword(s):  
Real Time ◽  
Water Demand ◽  
Water Distribution ◽  
Large Scale ◽  
Jacobian Matrix ◽  
Hessian Matrix ◽  
Demand Estimation ◽  
Matrix Inversion ◽  
Large Scale Network ◽  
Scale Network

Abstract Real-time modeling of the water distribution system (WDS) is a critical step for the control and operation of such systems. The nodal water demand as the most important time-varying parameter must be estimated in real-time. The computational burden of nodal water demand estimation is intensive, leading to inefficiency for the modeling of the large-scale network. The Jacobian matrix computation and Hessian matrix inversion are the processes that dominate the main computation time. To address this problem, an approach to shorten the computational time for the real-time demand estimation in the large-scale network is proposed. The approach can efficiently compute the Jacobian matrix based on solving a system of linear equations, and a Hessian matrix inversion method based on matrix partition and Iterative Woodbury-Matrix-Identity Formula is proposed. The developed approach is applied to a large-scale network, of which the number of nodal water demand is 12523, and the number of measurements ranging from 10 to 2000. Results show that the time consumptions of both Jacobian computation and Hessian matrix inversion are significantly shortened compared with the existing approach.

Image-based visual servoing with depth estimation

2021 ◽  
pp. 014233122110646
Author(s):  
Qingxuan Gongye ◽  
Peng Cheng ◽  
Jiuxiang Dong
Keyword(s):  
Real Time ◽  
State Vector ◽  
Visual Servoing ◽  
Jacobian Matrix ◽  
Fuzzy Controller ◽  
Image Plane ◽  
Depth Estimation ◽  
The State ◽  
Estimation Problem ◽  
Depth Information

For the depth estimation problem in the image-based visual servoing (IBVS) control, this paper proposes a new observer structure based on Kalman filter (KF) to recover the feature depth in real time. First, according to the number of states, two different mathematical models of the system are established. The first one is to extract the depth information from the Jacobian matrix as the state vector of the system. The other is to use the depth information and the coordinate point information of the two-dimensional image plane as the state vector of the system. The KF is used to estimate the unknown depth information of the system in real time. And an IBVS controller gain adjustment method for 6-degree-of-freedom (6-DOF) manipulator is obtained using fuzzy controller. This method can obtain the gain matrix by taking the depth and error information as the input of the fuzzy controller. Compared with the existing works, the proposed observer has less redundant motion while solving the Jacobian matrix depth estimation problem. At the same time, it will also be beneficial to reducing the time for the camera to reach the target. Conclusively, the experimental results of the 6-DOF robot with eye-in-hand configuration demonstrate the effectiveness and practicability of the proposed method.

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