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Over the past several years, researchers have made significant progress toward providing image guidance for the da Vinci system, utilizing data sources such as robot kinematic data, endoscope image data, and preoperative medical images. One data source that could provide additional subsurface information for use in image guidance is the da Vinci’s FireFly camera system. FireFly is a fluorescence imaging feature for the da Vinci system that uses injected indocyanine green dye and special endoscope filters to illuminate subsurface anatomical features as the surgeon operates. FireFly is now standard for many surgical procedures with the da Vinci robot; however, it is currently challenging to understand spatial relationships between pre-operative CT images and intraoperative fluorescence images. Here, we extend our image guidance system to incorporate FireFly information as well, so that the surgeon can view FireFly data in the image guidance display while operating with the da Vinci robot. We present a method for reconstructing 3D models of the FireFly fluorescence data from endoscope images and mapping the models into an image guidance display that also includes segmented, registered preoperative CT images. We analyze the accuracy of our reconstruction and mapping method and present a proof-of-concept application where we reconstruct a fluorescent subsurface blood vessel and map it into our image guidance display. Our method could be used to provide surgeons with additional context for the FireFly fluorescence imaging data or to provide additional data for computing or verifying the registration between the robot and preoperative images.

Partial nephrectomy involves removing a tumor while sparing surrounding healthy kidney tissue. Compared to total kidney removal, partial nephrectomy improves outcomes for patients but is underutilized because it is challenging to accomplish minimally invasively, requiring accurate spatial awareness of unseen subsurface anatomy. Image guidance can enhance spatial awareness by displaying a 3D model of anatomical relationships derived from medical imaging information. It has been qualitatively suggested that the da Vinci robot is well suited to facilitate image guidance through touch-based registration. In this paper we validate and advance this concept toward real-world use in several important ways. First, we contribute the first quantitative accuracy evaluation of touch-based registration with the da Vinci. Next, we demonstrate real-time, touch-based registration and display of medical images for the first time. Lastly, we perform the first experiments validating use of touch-based image guidance to improve a surgeon’s ability to localize subsurface anatomical features in a geometrically realistic phantom.

This paper investigates the effects of gamma radiation on the operation of commercially available capacitive microelectromechanical accelerometers intended for use in robotic systems deployed for nuclear disaster remediation. Radiation-induced accelerometer degradation is examined in terms of its effects on the input–output relationship of ADXL325 accelerometers (Analog Devices, Inc., Norwood, Massachusetts, USA) prior to sensor failure. Results show a moderate increase in sensor nonlinearity as well as significant, non-monotonic changes to accelerometer axis sensitivity and zero- $g$ bias. Both part-to-part variation and axis-to-axis variation within individual accelerometers are observed. The effects of the observed accelerometer degradation on the performance of a simple robotic manipulator that relies on acceleration feedback are evaluated in simulation. Additionally, using tools derived from adaptive control theory, this paper presents a real-time recalibration technique for mitigating the effects of the measured accelerometer degradation on the performance of robotic systems that can be applied in-field, without the knowledge of the degradation mechanisms. An example implementation of this technique is also evaluated. Results suggest that control-based strategies for mitigating hardware degradation may be able to extend the useful operating lifetime of non-radiation-hardened sensors in robotic systems deployed in extreme radiation environments.

This paper presents a general linear methodology for analyzing how the choice of electrical load affects stability and average power generation of an electromagnetic vibration energy harvester. Using bond graph techniques, the entire electromechanical harvesting system is modeled as a dynamically equivalent electrical circuit and ultimately recast as a feedback control system. This modeling approach enables the use of well-established linear control tools to assess the overall stability of the energy harvesting system. These tools are used to show: 1) why the load which would result in maximum power transfer from the harvester to the load, as established by the maximum power transfer theorem (MPTT), can only be achieved at a single frequency, and 2) how to ensure the system will always remain stable if the harvester is used in conjunction with an active load. Moreover, the presented modeling approach enables development of the power harvesting ratio—an analytical method for quantifying the harvester's power generation when multi-frequency excitation is involved. A custom harvester was constructed for experimental evaluation of the power harvesting ratio when varying: 1) the electrical load attached across the harvester leads and 2) the multifrequency vibrations used to excite the harvester.

Understanding the relationship between the impact of radiation at the component and system levels is challenging. This paper discusses a hierarchical approach, based on Bayesian theory, to establish a mechanism for determining system health based on the status of, and interactions between, the radiation response of component parts. When the Bayesian network is trained with a combination of experimental data, data from similar parts, simulations, and expert estimates, a quantitative estimate of the Total-Ionizing Dose (TID) response of a system can be obtained. Bayesian networks enable inference about system-level functional performance, the dose exposure, and the sensitivity of different components to TID, thus providing a framework for TID awareness in design and operation of systems. A case study of a robotic system consisting of commercial components is presented.

Background The recent development of MRI-guided laser-induced thermal therapy (LITT) offers a minimally invasive alternative to craniotomies performed for tumor resection or for amygdalohippocampectomy to control seizure disorders. Current LITT therapies rely on linear stereotactic trajectories that mandate twist-drill entry into the skull and potentially long approaches traversing healthy brain. The use of robotically-driven, telescoping, curved needles has the potential to reduce procedure invasiveness by tailoring trajectories to the curved shape of the ablated structure and by enabling access through natural orifices. Objective To investigate the feasibility of using a concentric tube robot to access the hippocampus through the foramen ovale to deliver thermal therapy and thereby provide a percutaneous treatment for epilepsy without drilling the skull. Methods The skull and both hippocampi were segmented from dual CT/MR image volumes for 10 patients. For each of the 20 hippocampi, a concentric tube robot was designed and optimized to traverse a trajectory from the foramen ovale to and through the hippocampus from head to tail. Results Across all 20 cases, the mean distances (error) between hippocampus medial axis and backbone of the needle were 0.55 mm, 1.11 mm, and 1.66 mm for best, mean, and worst case, respectively. Conclusion These curvilinear trajectories would provide accurate transforamenal delivery of an ablation probe to typical hippocampus volumes. This strategy has the potential to both decrease the invasiveness of the procedure and increase the completeness of hippocampal ablation.

Epilepsy is a prevalent neurological disorder affecting 65 million people globally [1]. Anti-epileptic medications fail to provide effective seizure control for 30% of patients, placing them at a 7–17% risk of Sudden Unexplained Death in Epilepsy and recurrent seizures. Surgical resection of the seizure focus is a potentially curative treatment for patients with seizures that electrophysiologically correlate to a focal lesion. For these patients, focal surgical resection can result in 60–70% seizure-freedom rates [2]. However, open resection carries the risk of cognitive impairment or focal neurologic deficit [3]. Recent innovations in MRI enable high resolution soft tissue visualization, and real-time temperature monitoring, making MR-guided ablation therapy a promising minimally invasive technique to restrict the tissue destruction to just the seizure focus. Commercial products (e.g., Visualase, Medtronic Inc.; ClearPoint, MRI Interventions Inc.; NeuroBlate, Monteris Inc.) have recently been introduced for MR-guided laser-based thermal ablation. These products require the physician drill a hole into the skull for ablation probe placement, and may not always be able to ablate the entire seizure focus when the structure has a curved shape (such as the hippocampus) [4]. Incomplete ablation of the seizure focus would lead to seizure recurrence. We have recently proposed concentric-tube steerable needles as a means to address these challenges [4–7]. They enable nonlinear trajectories and offer the potential to enter the brain through the patient’s cheek via a natural opening in the skull base (i.e. the foramen ovale). We have designed and fabricated an MR-compatible robotic system to provide high resolution actuation for helical needle deployment [5]. We have shown in simulation that the curved medial axis of hippocampus can be accessed via a helical needle that delivers the ablation probe into the brain [4]. These preliminary results suggest that MR-guided robotic transforamenal thermal therapy could potentially provide a less invasive approach for potentially curative epilepsy treatment. In this paper we present our first results delivering heat along curved paths in brain phantoms and imaging the resulting treatment zones using MRI.

The total-ionizing-dose robustness of low power microcontrollers is investigated. Experiments reveal that with increasing total ionizing dose (TID), the "Timing Window Vio- lations,"i.e., inability of the instruction set to execute within the clock-cycle(s) lead to failures in microcontroller operations. Clock frequency and supply voltage of the microcontroller are varied to determine the maximum clock frequency at which the micro- controller can execute software subroutines without failure. Low power microcontrollers from two different manufacturers were tested. The maximum clock frequency decreases with increasing TID for both parts. A model for the degradation based on analysis of circuit level timing models is presented. The microcontroller robustness implications for system designers and ASIC designers are discussed. TID has been shown to impact propagation delays in indi- vidual transistors (4), the timing characteristics of integrated circuits (5), memory access times (6), and propagation delays in CMOS flash-based FPGAs (7). In this work, timing window violations are experimentally demonstrated to be the primary source of failure in response to TID for a class of low power microcontrollers, and a model for the degradation and hard- ening implications are presented. The conclusion that timing window violations are the primary source of failure is supported by a measurement technique that allows insight into the in- ternal degradation of the device during the radiation exposure. The technique is necessary when information regarding indi- vidualtransistordegradation,themicrocontrollertechnology,or the fabrication process is not available, such as incorporating a COTS mechatronic subassembly including an integrated mi- crocontroller. Timing window violations are identified by per- forming a series of software tests on the microcontroller at var- ious frequencies and supply voltages. The technique to deter- mine the maximum and minimum frequencies and voltages for the microcontroller is more commonly used in electrical char- acterization (8). Results are presented for a commercially avail- able microcontroller, the Atmel ATMEGA328P (9). Analysis of the experimental results shows that the degradation is con- sistent with the expected degradation of logic gate switching time based on charge build-up in the gate oxide and shallow trench isolation (10). The results are further verified using a subset of the software tests on a Microchip PIC16F677 (11). The clock frequency measurement is nondestructive and can be monitored in a field deployment scenario to evaluate the health of the device, allowing for mission planning as well as life extensionthrough reducingclockoperating frequencyor in- creasing supply voltage.

Actuation redundancy in parallel mechanisms has been predominantly investigated assuming electromechanical actuators. Pneumatic actuation offers new alternatives to achieving stiffness modulation in parallel robots. This paper investigates the limits of stiffness modulation using two alternatives: modulation of joint-level stiffness using antagonistic pneumatic actuators (passive stiffness modulation) and stiffness modulation using antagonistic actuation at the structure level (active stiffness modulation). A surrogate translational parallel robot architecture, which is a variant of the Delta robot with one redundant kinematic chain, is used in this investigation. A simplified model of a pneumatic double-acting piston actuator is used to establish upper and lower bounds for attainable joint-level stiffness. A kinematic model of the parallel robot is presented along with its passive and active stiffness models. A simulation study is carried out assuming attainable joint-level stiffness based on the simplified pneumatic actuator model. The simulations show that, due to the achievable low pneumatic actuator stiffness, the active stiffness contribution can be as high as 65% of the passive stiffness within the robot workspace. This preliminary investigation suggests that pneumatic actuators are uniquely suited for robot interaction tasks (e.g. assembly or rehabilitation) where stiffness control and modulation can offer increased safety and task-specific end-effector stiffness.Copyright © 2015 by ASME

The temperature dependence of the maximum strain a bulk metallic glass (BMG) can undergo in its supercooled liquid state under specified conditions is determined. This formability is measured experimentally over a wide temperature range using Zr35Ti30Cu8.25Be26.75 as an example BMG. When considering five different BMG formers, we found that the formability continuously increases with temperature. This behavior is ubiquitous among BMGs whose crystallization behavior can be described by steady state nucleation and diffusion limited growth. Therefore, in order to maximize the formability during thermoplastic forming of BMGs, the highest processing temperature should be chosen at which crystallization can still be avoided.