Publications
390 results found
Zhao LC, Zhou T, Chang SD, et al., 2024, A disposable cup inspired smart floor for trajectory recognition and human-interactive sensing, Applied Energy, Vol: 357, ISSN: 0306-2619
Smart floor is an indispensable component of future smart buildings, it is urgent to develop a low-cost, self-powered, and high reliability smart floor. Herein, we propose a disposable cups inspired self-powered smart floor (DCIS-floor) for trajectory recognition and human-interactive sensing. The conical surface of the cup-shaped triboelectric nanogenerator (TENG) is greater than the projected area, resulting in an increased working area of functional materials on a limited floor. This enables more power generation units to be arranged on the limited floor while ensuring that each unit can generate sufficient electricity. Both pressure and shear force are applied as two conical surfaces contact, increasing the degree of contact between functional materials while avoiding excessive frictional force and wear during working process. Compared to cylindrical structures, conical structures offer greater flexibility in contact-separation without intricate machining and assembly, which is ideal for efficient large-area manufacturing. In the experiments, DCIS-floor achieves object motion trajectory recognition, visual recognition based trajectory wireless sensing, and pressure distribution sensing functions. Utilizing a convolutional neural network for data analysis, DCIS-floor realizes personnel identification. This work provides an effective method for smart floors in the safety monitoring, intelligent identification, and emergency rescue of future smart buildings.
Abdelaziz MEMK, Zhao J, Gil Rosa B, et al., 2024, Fiberbots: Robotic fibers for high-precision minimally invasive surgery, Science Advances, Vol: 10, ISSN: 2375-2548
Precise manipulation of flexible surgical tools is crucial in minimally invasive surgical procedures, necessitating a miniature and flexible robotic probe that can precisely direct the surgical instruments. In this work, we developed a polymer-based robotic fiber with a thermal actuation mechanism by local heating along the sides of a single fiber. The fiber robot was fabricated by highly scalable fiber drawing technology using common low-cost materials. This low-profile (below 2 millimeters in diameter) robotic fiber exhibits remarkable motion precision (below 50 micrometers) and repeatability. We developed control algorithms coupling the robot with endoscopic instruments, demonstrating high-resolution in situ molecular and morphological tissue mapping. We assess its practicality and safety during in vivo laparoscopic surgery on a porcine model. High-precision motion of the fiber robot delivered endoscopically facilitates the effective use of cellular-level intraoperative tissue identification and ablation technologies, potentially enabling precise removal of cancer in challenging surgical sites.
Li Y, Luo L, Kong Y, et al., 2024, A Point-of-Care Sensing Platform for Multiplexed Detection of Chronic Kidney Disease Biomarkers Using Molecularly Imprinted Polymers, Advanced Functional Materials, ISSN: 1616-301X
Chronic kidney disease (CKD) is one of the most serious non-communicable diseases affecting the population. In the early-stages patients have no obvious symptoms, until it becomes life-threatening leading end-stage kidney failure. Therefore, it is important to early diagnose CKD to allow therapeutic interventions and progression monitoring. Here, a point-of-care (POC) sensing platform is reported for the simultaneous detection of three CKD biomarkers, namely creatinine, urea, and human serum albumin (HSA), using reduced graphene oxide/polydopamine-molecularly imprinted polymer (rGO/PDA-MIP) fabricated with novel surface-molecularly imprinting technology. A multi-channel electrochemical POC readout system with differential pulse voltammetry (DPV) function is developed, allowing the simultaneous detection of the three biomarkers, in combination with the surface-MIP electrodes. This sensing platform achieves the record low limit-of-detection (LoD) at a femtomolar level for all three analytes, with wide detection ranges covering their physiological concentrations. Clinical validation is performed by measuring these analytes in serum and urine from healthy controls and patients with CKD. The average recovery rate is 81.8–119.1% compared to the results obtained from the hospital, while this platform is more cost-effective, user-friendly, and requires less sample-to-result time, showing the potential to be deployed in resource-limited settings for the early diagnosis and tracking progression of CKD.
Gil B, Wales D, Tan H, et al., 2023, Detection of medically relevant volatile organic compounds with graphene field-effect transistors and separated by low-frequency spectral and time signatures., Nanoscale, Vol: 16, Pages: 61-71
Exhaled human breath contains a mixture of gases including nitrogen, oxygen, carbon dioxide, water vapour and low molecular weight volatile organic compounds (VOCs). Different VOCs detected in human breath condensate have been recently related to several metabolic processes occurring inside body tissues in the pathological state, as candidate biomarkers for monitoring conditions such as lung injury, airway inflammation, immunity dysfunction, infection, and cancer. Current techniques for detecting these compounds include several types of mass spectroscopy, which are highly costly, time-consuming and dependent on trained personnel for sample analysis. The need for fast and label-free biosensors is paving the way towards the design of novel and portable electronic devices for point-of-care diagnosis with VOCs such as E-noses, and based on the measurement of signal signatures derived from their chemical composition. In this paper, we propose a device for VOC detection that was tested inside a controlled gas flow setup, resorting to graphene field-effect transistors (GFETs). Electrical measurements from graphene directly exposed to nitrogen plus VOC vapours involved cyclic measurements for the variation of graphene's resistance and low-frequency spectral noise in order to obtain distinctive signatures of the tested compounds in the time and frequency domains related, respectively, to Gutmann's theory for donor-acceptor chemical species and spectral sub-band analysis.
Arteaga JM, Sanchez J, Elsakloul F, et al., 2023, High frequency inductive power transfer through soil for agricultural applications, IEEE Transactions on Power Electronics, Vol: 38, Pages: 13415-13429, ISSN: 0885-8993
This paper presents 13.56 MHz inductive powertransfer (IPT) through soil for sensors in agricultural ap-plications. Two IPT system designs and their prototypes are presented. The first was designed for gathering data and observing the relationship between the performance of the coil driving circuits in response to water content, salinity, organic matter and compaction of the soil. The second prototype was designed as an application demonstrator, featuring IPT to an in-house sensor node enclosure buried 200 mm under the surface of an agricultural field. The results highlight that from the parameters studied, the combination of high salinity and high water content significantly increases the losses of the IPT system.The experiments demonstrate an over 40% rise in the losses from dc source to dc load after a 16% increase in soil water content and high salinity. In the technology demonstrator we mounted an IPT transmitter on a drone to wirelessly power an in-house bank of supercapacitors in the buried sensor-node enclosure. A peak power transfer of 30 W received at over 40% efficiency was achieved from a 22 V power supply on the drone to the energy storage under the ground. The coil separation in these experiments was 250 mm of which 200 mm correspond to the layer of soil. The coupling factor in all the experiments was lower than 5%. This system was trialled in the field for forty days andwireless power was performed five times throughout.
Gil B, Keshavarz M, Wales D, et al., 2023, Orthogonal Surface-Enhanced Raman Scattering/Field-Effect Transistor Detection of Breast and Colorectal Cancer-Derived Exosomes using Graphene as a Tag-Free Diagnostic Template, ADVANCED NANOBIOMED RESEARCH, ISSN: 2699-9307
Xiao B, Lam H-K, Xuan C, et al., 2023, Optimization for interval type-2 polynomial fuzzy systems: a deep reinforcement learning approach, IEEE Transactions on Artificial Intelligence, Vol: 4, Pages: 1269-1280, ISSN: 2691-4581
It is known that the interval type-2 (IT2) fuzzy controllers are superior compared to their type-1 counterparts in terms of robustness, flexibility, etc. However, how to conduct the type reduction optimally with the consideration of system stability under the fuzzy-model-based (FMB) control framework is still an open problem. To address this issue, we present a new approach through the membership-function-dependent (MFD) and deep reinforcement learning (DRL) approaches. In the proposed approach, the reduction of IT2 membership functions of the fuzzy controller is completing during optimizing the control performance. Another fundamental issue is that the stability conditions must hold subject to different type-reduction methods. It is tedious and impractical to resolve the stability conditions according to different type-reduction methods, which could lead to infinite possibility. It is more practical to guarantee the holding of stability conditions during type-reduction rather than resolving the stability conditions, the MFD approach is proposed with the imperfect premise matching (IPM) concept. Thanks to the unique merit of the MFD approach, the stability conditions according to all the different embedded type-1 membership functions within the footprint of uncertainty (FOU) are guaranteed to be valid. During the control processes, the state transitions associated with properly engineered cost/reward function can be used to approximately calculate the deterministic policy gradient to optimize the acting policy and then to improve the control performance through determining the grade of IT2 membership functions of the fuzzy controller. The detailed simulation example is provided to verify the merits of the proposed approach.
Yang SKE, Kiziroglou ME, Yeatman EM, et al., 2023, Acoustic flow sensor using a passive bell transducer, IEEE Sensors Journal, Vol: 23, Pages: 20553-20560, ISSN: 1530-437X
Sensing based on a passive transducer that is wirelessly linked to a nearby data collection node can offer an attractive solution for use in remote, inaccessible, or harsh environments. Here we report a pipe flow sensor based on this principle. A transducer mounted inside the pipe generates an acoustic signal that is picked up by an external microphone. The passive transducer comprises a cavity with a trapped ball that can oscillate in response to flow. Its collisions generate an acoustic signal correlated to the flow speed. The transducer is implemented on a 6 mm diameter probe and characterized as a water flow meter. The time - average microphone voltage output is calculated by an analogue circuit, without any further signal processing. With the microphone mounted on the probe, and for flow rates in the range 0.35 m/s to 6.5 m/s, correlation between the sensor voltage output and flow rate data from a commercial flow meter is demonstrated with a worst-case accuracy of 2%. This was achieved by simple averaging of the acoustic pulse train over a 5-second time interval. Consistent correlation with the microphone mounted on the pipe wall at distances up to 150 mm from the probe location is also reported. These results demonstrate the viability of remote acoustic flow sensing using passive structures and offer a simple and minimally invasive flow monitoring method.
Wright SW, Kiziroglou ME, Yeatman EM, 2023, Inductive power line harvester with flux guidance for self-powered sensors, IEEE Sensors Journal, Vol: 23, Pages: 20474-20482, ISSN: 1530-437X
Self-powered sensors are expected to enable new large-scale deployment and location access capabilities for sensor systems. Energy harvesting devices have been shown to provide adequate power densities but their dependence on very specific environmental conditions restricts their applicability. Energy harvesting from power line infrastructure offers an architecture for addressing this challenge, because such infrastructure is widely available. In this paper an inductive power line harvester concept is presented, based on a flux concentration approach adapted to a closed-loop core geometry. Flux concentration is studied by simulation, showing a 26% flux increase using a 1:3 geometrical concentration ratio in a closed-loop core. A 20×20×25 mm prototype with a U-shaped soft-core sheet and a 200-turn Cu coil around a 5 mm diameter, 20 mm long soft-core rod is introduced. The total device volume is 9.1 cm 3 . Characterization results on a power line evaluation setup for currents up to 35 A RMS and a 50 Hz – 1 kHz range are presented. Power between 2.2 mW (50 Hz) and 233 mW (1 kHz) is demonstrated on an ohmic load, from a 10 A RMS power line current, employing impedance matching with reactance cancellation. The corresponding power densities are 0.24 mW/cm 3 and 25 mW/cm 3 respectively, per total device volume. This performance is adequate for enabling self-powered wireless sensor networks installed along power distribution lines.
Sun L, Ma N, Xiao B, et al., 2023, Adaptive Robust Fault-Tolerant Regulation of Mechatronic Systems with Prescribed-Time Convergence, Pages: 3552-3557
In this paper, we propose a synchronized prescribed-time control strategy for a class of nonlinear mechatronic systems with external disturbance, actuation saturation, and actuator faults, which features simultaneous translational and rotational motion tracking in the same prescribed time. Dual quaternion is employed to model the coupling effect between translational and rotational motions, which provides a unified representation for describing multiple degree-of-freedom motions. In addition, online adaptive technology is incorporated for real-time monitoring and separation of actuator failure information. The adaptive capability of the controller to parameter perturbation, disturbance, and fault deviation is therefore enhanced. Furthermore, the closed-loop system is featured by L2 gain stability/robustness against thrust output deviation, while the system trajectory is guaranteed to converge with user-defined settling time. Finally, numerical simulations on a microsatellite platform with redundant thrusters are performed to verify the effectiveness of the proposed fault-tolerant control approach.
Kim JA, Hou Y, Keshavarz M, et al., 2023, Characterization of bacteria swarming effect under plasmonic optical fiber illumination, Journal of Biomedical Optics, Vol: 28, Pages: 1-15, ISSN: 1083-3668
SignificancePlasmo-thermo-electrophoresis (PTEP) involves using plasmonic microstructures to generate both a large-scale convection current and a near-field attraction force (thermo-electrophoresis). These effects facilitate the collective locomotion (i.e., swarming) of microscale particles in suspension, which can be utilized for numerous applications, such as particle/cell manipulation and targeted drug delivery. However, to date, PTEP for ensemble manipulation has not been well characterized, meaning its potential is yet to be realized.AimOur study aims to provide a characterization of PTEP on the motion and swarming effect of various particles and bacterial cells to allow rational design for bacteria-based microrobots and drug delivery applications.ApproachPlasmonic optical fibers (POFs) were fabricated using two-photon polymerization. The particle motion and swarming behavior near the tips of optical fibers were characterized by image-based particle tracking and analyzing the spatiotemporal concentration variation. These results were further correlated with the shape and surface charge of the particles defined by the zeta potential.ResultsThe PTEP demonstrated a drag force ranging from a few hundred fN to a few tens of pN using the POFs. Furthermore, bacteria with the greater (negative) zeta potential ( | ζ | > 10 mV) and smoother shape (e.g., Klebsiella pneumoniae and Escherichia coli) exhibited the greatest swarming behavior.ConclusionsThe characterization of PTEP-based bacteria swarming behavior investigated in our study can help predict the expected swarming behavior of given particles/bacterial cells. As such, this may aid in realizing the potential of PTEP in the wide-ranging applications highlighted above.
Blagojevic M, Dieudonne A, Kamecki L, et al., 2023, Autonomous electrical current monitoring system for aircraft, IEEE Transactions on Aerospace and Electronic Systems, Vol: 59, Pages: 3345-3358, ISSN: 0018-9251
Aircraft monitoring systems offer enhanced safety, reliability, reduced maintenance cost and improved overall flight efficiency. Advancements in wireless sensor networks (WSN) are enabling unprecedented data acquisition functionalities, but their applicability is restricted by power limitations, as batteries require replacement or recharging and wired power adds weight and detracts from the benefits of wireless technology. In this paper, an energy autonomous WSN is presented for monitoring the structural current in aircraft structures. A hybrid inductive/hall sensing concept is introduced demonstrating 0.5 A resolution, < 2% accuracy and frequency independence, for a 5 A – 100 A RMS, DC-800 Hz current and frequency range, with 35 mW active power consumption. An inductive energy harvesting power supply with magnetic flux funnelling, reactance compensation and supercapacitor storage is demonstrated to provide 0.16 mW of continuous power from the 65 μT RMS field of a 20 A RMS, 360 Hz structural current. A low-power sensor node platform with a custom multi-mode duty cycling network protocol is developed, offering cold starting network association and data acquisition/transmission functionality at 50 μW and 70 μW average power respectively. WSN level operation for 1 minute for every 8 minutes of energy harvesting is demonstrated. The proposed system offers a unique energy autonomous WSN platform for aircraft monitoring.
Wang Z, Lam H-K, Guo Y, et al., 2023, Adaptive Event-Triggered Control for Nonlinear Systems With Asymmetric State Constraints: A Prescribed-Time Approach, IEEE TRANSACTIONS ON AUTOMATIC CONTROL, Vol: 68, Pages: 3625-3632, ISSN: 0018-9286
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- Citations: 4
Becker T, Kiziroglou ME, Duffy M, et al., 2023, Industrial Adoption of Energy Harvesting: Challenges and Opportunities, IEEE POWER ELECTRONICS MAGAZINE, Vol: 10, Pages: 57-64, ISSN: 2329-9207
Liu M, Zhang Y, Fu H, et al., 2023, A seesaw-inspired bistable energy harvester with adjustable potential wells for self-powered internet of train monitoring, APPLIED ENERGY, Vol: 337, ISSN: 0306-2619
Zhou X, Yang Z, Ren Y, et al., 2023, Modified Bilateral Active Estimation Model: A Learning-Based Solution to the Time Delay Problem in Robotic Tele-Control, IEEE ROBOTICS AND AUTOMATION LETTERS, Vol: 8, Pages: 2653-2660, ISSN: 2377-3766
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- Citations: 1
Li X, Keshavarz M, Kassanos P, et al., 2023, SERS detection of breast cancer-derived exosomes using a nanostructured Pt-black template, Advanced Sensor Research, Vol: 4, Pages: 1-12, ISSN: 2751-1219
At present, there are no cancer treatments that are both non-invasive and highly accurate. New tests that can diagnose cancer at an early stage would help to facilitate such improved therapies, and many recent studies have focused on the development of liquid biopsy tests for this purpose. Exosomes are extracellular vesicles secreted by cells as a means of communication that can be simply collected from blood samples. Current studies have shown the potential of surface-enhanced Raman spectroscopy (SERS) in differentiating cancerous cells from healthy cells. Herein, a bespoke platinum-black (Pt-black) SERS template is developed—via a cost-effective fabrication method of electroplating—to detect malfunctioned (cancerous) exosomes. The results demonstrate that the Pt-black SERS substrate exhibits stable and consistent spectra, which produces the high reproducibility required for a reliable diagnostic template. More importantly, using the Pt-black SERS template allows for the differentiation of cancer-derived exosomes (extracted from 4T1 cells—a triple-negative breast cancer cell line) and exosomes from healthy fibroblast cells with an 83.3% sensitivity and a 95.8% specificity. This study establishes the potential of the Pt-black template in detecting cancerous exosomes and lays a solid foundation for future studies in the clinical application of SERS in cancer diagnosis.
Chen X, Zhao J, Vyas K, et al., 2023, Origami-inspired flexure-based robot for endomicroscopy probe manipulation, The 22nd International Conference on Solid-State Sensors, Actuators and Microsystems, Publisher: IEEE
Probe-based confocal endomicroscopy (pCLE) is apromising imaging modality but requires precise andcontrolled scanning over the tissue surface, which issignificantly challenging to the operator. The paperpresents a 3D-printed origami-inspired miniature deltarobot for accurate manipulation of pCLE probe.Kinematics and Finite Element Analysis (FEA) simulationare conducted for a transfer matrix from the applied voltageto the displacement. An open-loop kinematiccharacterization based on the simulation was performed.The results demonstrate adequate repeatability andprecision, allowing the execution of various motions.Further 3D motion control will be achieved by employingvisual servoing.
Shi M, Zhang Y, Guo X, et al., 2023, Microstructure-enhanced vision-based tactile sensor, 22nd International Conference on Solid-State Sensors, Actuators and Microsystems (Transducers 2023)
This paper presents for the first time a vision-based tactile sensor (VBTS) enhanced by micro-structured features. Differing from conventional designs where tracking markers are added to unmodified structures, here an interface surface is constructed with micromachined trenches, which allow varying amounts of light to transmit according to the applied force, forming a matrix of bright cross-shaped patterns on the bottom surface. The variation of brightness, wire width, and location of the cross patterns was captured by a camera and used to sense force magnitude and contact location.Compared to previously reported VBTSs, this microstructured sensor increases the sensitivity by magnifying the visual effect of shape distortion. With theoretical and experimental analysis, this sensor achieved a sensitivity of 20 mN. The resolution reached 1 mm for single-point touch. This sensor is entirely soft and compatible with soft robots and wearable electronics. Unlike piezoelectric sensor arrays, it is immune to electrical crosstalk and interference.
Sun L, Huang Y, Fei H, et al., 2023, Fixed-time regulation of spacecraft orbit and attitude coordination with optimal actuation allocation using dual quaternion, FRONTIERS IN ROBOTICS AND AI, Vol: 10, ISSN: 2296-9144
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- Citations: 1
Wright SW, Kiziroglou ME, Yeatman EM, 2023, Clamped closed-loop flux guides for power line inductive harvesting, 2022 21st International Conference on Micro and Nanotechnology for Power Generation and Energy Conversion Applications (PowerMEMS), Publisher: IEEE, Pages: 82-85
Inductive harvesting from existing power lines in vehicle, industrial and infrastructure environments offers an opportunity for providing energy autonomy to sensors in a wide range of environments with high sensing interest. Flux funnelling has been shown to improve the power density of such devices by over an order of magnitude. The requirement for retrofitting onto existing power lines leads to a demand for detachable magnetic core interfaces, which introduce gaps and uncertainty to device performance. In this paper, an inductive energy harvesting device design that addresses this challenge is introduced. The design allows the interfaces to be internal to the device housing. Repeatable fixing, with reduced sensitivity to installation practicalities and controllable force is achieved by a screw-pressing mechanism, and the employment of a hard polyoxymethylene housing material. This method is utilized in an inductive power-line prototype, demonstrating power output up to 260 mW from a 40 A RMS, 500 Hz current, emulating aircraft power lines.
Zhang D, Gorochowski TE, Marucci L, et al., 2023, Advanced medical micro-robotics for early diagnosis and therapeutic interventions, Frontiers in Robotics and AI, Vol: 9, Pages: 1-19, ISSN: 2296-9144
Recent technological advances in micro-robotics have demonstrated their immense potential for biomedical applications. Emerging micro-robots have versatile sensing systems, flexible locomotion and dexterous manipulation capabilities that can significantly contribute to the healthcare system. Despite the appreciated and tangible benefits of medical micro-robotics, many challenges still remain. Here, we review the major challenges, current trends and significant achievements for developing versatile and intelligent micro-robotics with a focus on applications in early diagnosis and therapeutic interventions. We also consider some recent emerging micro-robotic technologies that employ synthetic biology to support a new generation of living micro-robots. We expect to inspire future development of micro-robots toward clinical translation by identifying the roadblocks that need to be overcome.
Ge I, Jiang Y, Dankwort T, et al., 2023, MEMS AlN Piezoelectric Beams with Integrated NdFeB Magnets for Power Line and Rotational Motion Energy Harvesting, Pages: 122-125
On-chip power autonomy is a central objective of energy harvesting technologies. The integration of piezoelectric and magnetic materials with silicon-processing could address proof-mass size and broadband motion operation limitations. In this work, a MEMS device combining a silicon-based, AlN piezoelectric beam with an integrated NdFeB tip magnet is proposed as an energy harvesting transducer. The device is evaluated for rotational motion and power line energy harvesting use cases. In the rotational motion evaluation, a voltage output peak of 0.35 V is demonstrated from a permanent magnet passing at 4 mm distance. In the power line evaluation, an output power delivery of 5 μW on an ohmic load is demonstrated, at 10 mm distance from a power line carrying an RMS current of 13 A. These results show promising performance towards micro-chip integrated energy autonomy, suitable for time-varying magnetic field and relative structural motion environments.
Chen X, Halvorsen E, Kiziroglou ME, et al., 2023, A Position Control Modeling Method for an Origami-Inspired Flexure-Based Piezoelectric-Actuated Manipulator, Pages: 171-174
The manuscript presents a modelling method for position control of a piezoelectric-Actuated compliant mechanism. The method involves pseudo-rigid body (PRB) theory, linear electromechanical model of piezoelectric benders and Simulink-based simulation. In order to validate the modelling method, two experiments were designed and conducted. They are working volume estimation and voltage clip recurrence. The comparison between simulation and experimental results indicates that the modelling can predict the motion of the compliant structure and be used for optimization design. In future work, the model can be extended to include the hysteresis model of piezoelectric materials. Besides, the model can be applied together with an onboard visual feedback system to carry out a closed-loop control for higher precision motion.
Xiao B, Hong W, Wang Z, et al., 2023, Learning-Based Inverse Kinematics Identification of the Tendon-Driven Robotic Manipulator for Minimally Invasive Surgery, ISSN: 2162-4704
It is well-known that the tendon-driven robotic manipulator plays an important role in robotic-assisted minimally invasive surgery (MIS). However, due to the intrinsic nonlinearities, uncertainties, slack and hysteresis introduced by the tendon-driven actuation, the tendon-driven robotic manipulator is difficult to model and control when compared with the traditional actuation styles. To serve the modeling purpose, in this paper, the deep-learning-based intelligent modeling of inverse kinematics in the snake-like tendon-driven surgical instrument is presented. In the proposed approach the Deep Recurrent Neural Network (DRNN) with Long Short-Term Memory (LSTM) architecture is adopted to memorize and identify the nonlinear inverse kinematics of the tendon-driven surgical instrument through the history of the motor and tip positions. To collect highly reliable data to train the DRNN, the experiment to generate training data is carefully designed with the consideration of the stainless tendon characters and motor limitations. During the designed controller movements, the kinematics data is obtained by recording the motor positions and the tip positions. Besides, it is noticed that there are correlations of the sequential data samples, which could significantly reduce the modeling accuracy. To remove the correlations and improve the modeling performance, the correlations of the sequential data samples are removed by modifying the training processes. Modeling results and detailed discussions verified the effectiveness of the proposed approach.
Kiziroglou ME, Yeatman EM, 2023, Energy Harvesters and Power Management, More-than-Moore Devices and Integration for Semi Conductors, Pages: 1-46, ISBN: 9783031216091
Energy harvesting is a subset of Renewable Energy Technologies. It regards specifically the collection of small amounts of ambient energy, typically in the milliwatt range and below, for local use with the objective of providing energy autonomy to microsystems. In this chapter, an overview of the most common energy harvesting methods is presented, including motion, heat and electromagnetic field energy sources. A brief summary of solar, acoustic and radio frequency wave energy harvesting technologies is also presented. Finally, an overview of the main power management technologies developed and employed in energy harvesting is provided. The current state of the art provides adequate tools for developing energy autonomous microsystems in specific applications. Research focusing on integrating these technologies in low-power microchips, for energy autonomous operation in important application environments, such as on the human body or around a mobile phone, could enable new interactive capabilities for electronic information systems within the next 5 years.
Blagojevic M, Dieudonne A, Kamecki L, et al., 2023, The AMPWISE Project, Pages: 174-177
This paper presents an energy autonomous Wireless Sensor Network (WSN) for monitoring the structural current in aircraft structures. A hybrid inductive/hall sensing concept is introduced demonstrating 0.5 A resolution, 2% accuracy and frequency independence, for a 5 A-100 A Root-Mean-Square (RMS), DC-800 Hz current and frequency range, with 35 mW active power consumption. An inductive energy harvesting power supply with magnetic flux funneling, reactance compensation and supercapacitor storage is demonstrated to provide 0.16 mW of continuous power from the 65 uT RMS field of a 20 A RMS, 360 Hz structural current. A low-power sensor node platform with a custom multi-mode duty cycling network protocol is developed, offering cold starting network association and data acquisition/transmission functionality at 50 uW and 70 uW average power respectively. WSN level operation for 1 minute for every 8 minutes of energy harvesting is demonstrated.
Holmes AS, Yang SKE, Kiziroglou ME, et al., 2022, Miniaturized wet-wet differential pressure sensor, IEEE Sensors Conference, Publisher: IEEE, ISSN: 1930-0395
We report a miniaturized wet-wet differential pressure sensor with applications in pressure and flow sensing in water networks and other harsh environments. The device is similar in concept to a conventional wet-wet differential pressure sensor in that the sensing element is protected from the external environment by oil-filled cavities closed off by corrugated diaphragms. However, with a package envelope of 11.0 x 4.8 x 3.4 mm 3 , corresponding to a volume of only 0.18 cm 3 , the device is considerably smaller than commercially available wet-wet differential pressure sensors. A high degree of miniaturization has been achieved by using micromachining to fabricate the corrugated diaphragms. Preliminary experimental results are presented showing operation of the device as a delta-pressure flow speed sensor in a water flow test rig.
Cursi F, Bai W, Yeatman EMM, et al., 2022, Task Accuracy Enhancement for a Surgical Macro-Micro Manipulator With Probabilistic Neural Networks and Uncertainty Minimization, IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, ISSN: 1545-5955
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Cursi F, Bai W, Yeatman EM, et al., 2022, Optimization of surgical robotic instrument mounting in a macro-micro manipulator setup for improving task execution, IEEE Transactions on Robotics, Vol: 38, Pages: 2858-2874, ISSN: 1552-3098
In Minimally Invasive Robotic Surgery (MIRS),the surgical instrument is usually inserted inside the patient’sbody through a small incision, which acts as a Remote Centerof Motion (RCM). Serial-link manipulators can be used asmacro robots on which micro surgical robotic instruments aremounted to increase the number of degrees of freedom (DOFs)of the system and ensure safe task and RCM motion execution.However, the surgical instrument needs to be placed in anappropriate configuration when completing the motion tasks.The contribution of this work is to present a novel frameworkthat preoperatively identifies the best base configuration, interms or Roll, Pitch, and Yaw angles, of the micro surgicalinstrument with respect to the macro serial-link manipulator’send-effector in order to achieve the maximum accuracy anddexterity in performing specified tasks. The framework relieson Hierarchical Quadratic Programming (HQP) for the control,Genetic Algorithm (GA) for the optimization, and on a resilienceto error strategy to make sure deviations from the optimum donot affect the system’s performance.Simulation results show that the mounting configuration ofthe surgical instrument significantly impacts the performanceof the whole macro-micro manipulator in executing the desiredmotion tasks, and both the simulation and experimental resultsdemonstrate that the proposed optimization method improves theoverall performance.
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