Month: April 2018

Dynamic decoupling control of DGCMG gimbal system via state feedback linearization

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Abstract
To radically eliminate the influence of coupling torque caused by gyroscopic effects on system stability and precision and to improve the high precision performance of the low speed gimbal servo system in a double gimbal control moment gyro (DGCMG), this paper proposes a novel composite controller design method combining state feedback linearization and adaptive sliding mode control method. The precision problem caused by residual coupling and nonlinear friction have been successfully solved by introducing an adaptive sliding mode compensator. Simulation and experimental results show that the proposed method realizes dynamics decoupling of gimbal system and enhances system robustness against parameter change and external disturbance
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Fabrication of Patient-Specific Intracranial Aneurysm Models for Burst Testing

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Abstract

A cerebral or intracranial aneurysm (ICA) is a condition that is defined as a local dilation of an artery in the brain due to locally weakened blood vessel walls. This creates a balloon-shaped bulge in the thin artery wall that can rupture, and the ensuing subarachnoid hemorrhage can cause a stroke, coma, or even death. Therefore, it is of interest to understand how ICAs grow and eventually rupture in order to develop earlier diagnosis or treatment techniques. Current imaging technologies include computed tomography and magnetic resonance imaging, which can be used to generate three-dimensional computer-assisted design models. However, these 3D models only provide the shape of the ICA and monitory macroscopic growth of aneurysms, but are too low resolution to determine the specific wall thickness of vasculature. Aneurysms tend to rupture at the thinnest point in the vessel wall, but it is difficult to predict rupture location from just 3D geometry alone using a CT scan reconstruction.

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A Skull-Mounted Robot with a Compact and Lightweight Parallel Mechanism for Positioning in Minimally Invasive Neurosurgery

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Abstract

Robotic systems play an increasingly important role in improving feasibility and effectiveness of minimally invasive neurosurgery (MIN). However, large footprint, bulky size, and complex mechanisms limit the clinical application of existing robotic neurosurgery solutions. This paper proposes a novel skull-mounted robot with a compact and lightweight parallel mechanism for positioning of surgical tools in MIN. The system serves as a mechanical guide for automatic positioning of needles, catheters, probes, or electrodes. A parallel mechanism with 4 degrees of freedom (DOFs) is adopted, with the aim of providing sufficient accuracy and load capacity. The volume of the robot is only 50 mm ร— 50 mm ร— 40 mm and the weight is 73 g. The miniature design allows the robot to be mounted on the skull easily without consuming space in the operating room while avoiding the patientโ€™s immobilization, simplifying the registration operation, and increasing patient comfort and tolerability. The mechanical design, kinematics and workspace are analyzed and described in detail. Three experiments on the prototype are conducted to test the stiffness, accuracy and performance. Results show that the deflection is less than 0.1 mm for holding common surgical tools and the tracking errors are less than 1.2 mm and 1.9ยฐ which is acceptable for MIN. The robot can be easily and firmly mounted on the skull model and cadaver head, and flexibly manipulated on the skull model.
 

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Finite Time Fault Tolerant Control for Robot Manipulators Using Time Delay Estimation and Continuous Nonsingular Fast Terminal Sliding Mode Control

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Abstract
In this paper, a novel finite time fault tolerant control (FTC) is proposed for uncertain robot manipulators with actuator faults. First, a finite time passive FTC (PFTC) based on a robust nonsingular fast terminal sliding mode control (NFTSMC) is investigated. Be analyzed for addressing the disadvantages of the PFTC, an AFTC are then investigated by combining NFTSMC with a simple fault diagnosis scheme. In this scheme, an online fault estimation algorithm based on time delay estimation (TDE) is proposed to approximate actuator faults. The estimated fault information is used to detect, isolate, and accommodate the effect of the faults in the system. Then, a robust AFTC law is established by combining the obtained fault information and a robust NFTSMC. Finally, a high-order sliding mode (HOSM) control based on super-twisting algorithm is employed to eliminate the chattering. In comparison to the PFTC and other state-of-the-art approaches, the proposed AFTC scheme possess several advantages such as high precision, strong robustness, no singularity, less chattering, and fast finite-time convergence due to the combined NFTSMC and HOSM control, and requires no prior knowledge of the fault due to TDE-based fault estimation. Finally, simulation results are obtained to verify the effectiveness of the proposed strategy. Index Termsโ€”Fault diagnosis (FD), fault tolerant control (FTC), robot manipulators, terminal sliding mode, time delay estimation (TDE).
 
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Ultrasound-Assisted Guidance With Force Cues for Intravascular Interventions

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Image guidance during minimally invasive intravascular interventions is primarily achieved based on X-ray fluoroscopy, which has several limitations including limited 3-D imaging capability, significant doses of radiation to operators, and lack of contact force measurement between the cardiovascular tissue and interventional tools. Ultrasound imaging can be adopted to complement or possibly replace 2-D fluoroscopy for intravascular interventions due to its portability, safety to use, and the ability of providing depth information. However, it is challenging to precisely visualize catheters and guidewires in the ultrasound images. In this paper, we propose a novel method to figure out both the position and orientation of the catheter tip in 2-D ultrasound images in real time by detecting and tracking a passive marker attached to the catheter tip. Moreover, the contact force can be estimated simultaneously as well via measuring the length variation of the marker. A geometrical model-based method is introduced to detect the initial position of the marker, and a Kanade-Lucas-Tomasi-based algorithm is developed to track the position, orientation, and length of the marker. The ex vivo experiment results validate the effectiveness of the proposed approach in automatically locating the catheter tip in ultrasound images and its capability of sensing the contact force. Therefore, it can be concluded that the presented method can be utilized to better facilitate operators during intravascular interventions.

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