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IEEE/ASME (AIM) International Conference on Advanced Intelligent Mechatronics

作者： Hen-Wei Huang Jack Chen Philipp Rupp Claas Ehmke Peter R Chai Riya Dhar Ian Ballinger Giovanni Traverso Division of Medicine Brigham & Women’s Hospital Harvard Medical School Boston MA USA The Koch Institute for Integrative Cancer Research Massachusetts Institute of Technology Cambridge MA USA Department of Mechanical Engineering Massachusetts Institute of Technology Cambridge MA USA Department of Mechanical and Process Engineering Multi-Scale Robotics Lab ETH Zurich Tannenstrasse 3 Zurich Switzerland Department of Emergency Medicine Brigham & Women’s Hospital Harvard Medical School Boston MA USA

ISBN: (数字)9798350355369

ISBN: (纸本)9798350355376

The COVID-19 pandemic renewed interest in contactless vital signs monitoring using computer vision to efficiently screen for disease symptoms. These vital signs monitoring systems have been deployed in either surveillance camera systems or robotic systems. Despite initially promising results, there has been limited uptake. Surveillance cameras are static, which requires subjects to remain inside their field of view during measurement, thus limiting their capacity for continuous monitoring. Robotic systems are mobile and can autonomously track subjects during measurement, but they require expensive software and hardware and tend not to be scalable. In this work, we propose a cost-effective and scalable robotic solution using machine vision microcontrollers to capture photoplethysmography (PPG) information on ambulatory subjects. We characterize the performance of our camera system to design an optimized machine vision protocol to maximize the performance of the machine vision microcontroller for vital signs monitoring. We compared the heart rate estimation accuracy of our cost-effective solution against a state-of-the-art camera (FLIR Blackfly). Our solution achieves a mean average error of 5.0 BPM, comparable to the FLIR Blackfly’s mean average error of 4.7 BPM while keeping social distancing (at least 2 meters between cameras and subjects). The major contribution of this work is the design of a machine vision protocol that enables a cost-effective, scalable, and mobile system to achieve the same heart rate estimation accuracy as current state-of-the-art methods.

关键词： Heart rate Protocols Accuracy Microcontrollers Machine vision Surveillance Robot vision systems

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Strain-sensitive flexible magnetoelectric ceramic nanocomposites

arXiv

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arXiv 2022年

作者： Kim, Minsoo Kim, Donghoon Aktas, Buse Choi, Hongsoo Puigmartí-Luis, Josep Nelson, Bradley J. Chen, Xiang-Zhong Pané, Salvador Multi-Scale Robotics Lab Institute of Robotics and Intelligence Systems ETH Zurich Tannenstrasse 3 Zurich8092 Switzerland Daegu Korea Republic of Department of Physical Chemistry Institut de Química Teòrica i Computacional University of Barcelona Martí i Franquès 1 Barcelona08028 Spain Pg. Lluís Companys 23 Barcelona08010 Spain

Advanced flexible electronics and soft robotics require the development and implementation of flexible functional materials. Magnetoelectric (ME) oxide materials can convert magnetic input into electric output and vice versa, making them excellent candidates for advanced sensing, actuating, data storage, and communication. However, their application has been limited to rigid devices due to their brittle nature. Here, we report flexible ME oxide composite (BaTiO3/CoFe2O4) thin film nanostructures that can be transferred onto a stretchable substrate such as polydimethylsiloxane (PDMS). In contrast to rigid bulk counterparts, these ceramic nanostructures display a flexible behavior and exhibit reversibly tunable ME coupling via mechanical stretching. We believe our study can open up new avenues for integrating ceramic ME composites into flexible electronics and soft robotic devices. © 2022, CC BY.

关键词： Silicones

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Pose-Estimate-Based Target Tracking for Human-Guided Remote Sensor Mounting with a UAV

Pose-Estimate-Based Target Tracking for Human-Guided Remote ...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Daniel R. McArthur Ze An David J. Cappelleri Multi-Scale Robotics and Automation Lab School of Mechanical Engineering Purdue University West Lafayette IN USA

ISBN: (数字)9781728173955

ISBN: (纸本)9781728173962

In this paper, we present a method for pose-estimate-based target tracking (PBTT) that enables the performance of autonomous aerial manipulation operations in unstructured environments using fully on-board computation for both UAV localization and target tracking. The PBTT method does not depend on extracting traditional visual features (e.g. using SIFT, SURF, ORB, etc.) on or near the target. Instead, the algorithm combines input from an RGB-D camera and the UAV's position estimator (which utilizes a downward-facing optical flow camera for horizontal localization) to track a target point selected by a human operator. The effectiveness of the PBTT method is evaluated through several autonomous flight tests performed with the Interacting-Boomcopter (I-BC) UAV platform in unstructured environments and in the presence of light wind disturbances.

关键词： Target tracking Cameras Unmanned aerial vehicles Visualization Task analysis Surface cleaning Three-dimensional displays

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PaintPath: Defining Path Directionality in Maps for Autonomous Ground Vehicles

PaintPath: Defining Path Directionality in Maps for Autonomo...

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2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Riley Bowyer Thomas Lowe Paulo Borges Tirthankar Bandyopadhyay Tobias Löw David Haddon Robotics and Autonomous Systems Group Data61 CSIRO Brisbane Australia Multi-Scale Robotics Lab ETH Zürich Zurich Switzerland

ISBN: (数字)9781728162126

ISBN: (纸本)9781728162133

Directionality in path planning is essential for efficient autonomous navigation in a number of real-world environments. In many map-based navigation scenarios, the viable path from a given point A to point B is not the same as the viable path from B to A. We present a method that automatically incorporates preferred navigation directionality into a path planning costmap. This `preference' is represented by coloured paths in the costmap. The colourisation is obtained based on an analysis of the driving trajectory generated by the robot as it navigates through the environment. Hence, our method augments this driving trajectory by intelligently colouring it according to the orientation of the robot during the run. Creating an analogy between the vehicle orientation angle and the hue angle in the Hue-Saturation-Value colour space, the method uses the hue, saturation and value components to encode the direction, directionality and scalar cost, respectively, into a costmap image. We describe a costing function to be used by the A* algorithm to incorporate this information to plan direction-aware vehicle paths. Our experiments with LiDAR-based localisation and autonomous driving in real environments illustrate the applicability of the method.

关键词： Space vehicles Navigation Costing Image color analysis Trajectory Planning Autonomous robots

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Giant shape-memory effect in twisted ferroic nanocomposites

arXiv

引用

arXiv 2022年

作者： Kim, Donghoon Kim, Minsoo Reidt, Steffen Han, Hyeon Choi, Hongsoo Puigmartí-Luis, Josep Trassin, Morgan Nelson, Bradley J. Chen, Xiang-Zhong Pané, Salvador Multi-Scale Robotics Lab Institute of Robotics and Intelligence Systems ETH Zurich Tannenstrasse 3 Zurich8092 Switzerland IBM Research Zurich Säumerstrasse 4 Rüschilikon 8803 Switzerland 06120 Germany Daegu Korea Republic of Department of Physical Chemistry University of Barcelona Martí i Franquès 1 Barcelona08028 Spain Pg. Lluís Companys 23 Barcelona08010 Spain Department of Materials ETH Zurich Zurich8093 Switzerland

The shape recovery ability of shape-memory alloys vanishes below a critical size (~50nm), which prevents their practical applications at the nanoscale. In contrast, ferroic materials, even when scaled down to dimensions of a few nanometers, exhibit actuation strain through domain switching, though the generated strain is modest (~1%). Here, we develop free-standing twisted architectures of nanoscale ferroic oxides showing shape-memory effect with a giant recoverable strain (>10%). The twisted geometrical design amplifies the strain generated during ferroelectric domain switching, which cannot be achieved in bulk ceramics or substrate-bonded thin films. The twisted ferroic nanocomposites allow us to overcome the size limitations in traditional shape-memory alloys and opens new avenues in engineering large-stroke shape-memory materials for small-scale actuating devices such as nanorobots and artificial muscle fibrils. © 2022, CC BY.

关键词： Ferroelectricity

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Biomechanical study of living caenorhabditis elegans embryos using cellular force microscopy 23

Biomechanical study of living caenorhabditis elegans embryos...

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23rd International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2019

作者： Krenger, Roger Burri, Jan T. Lehnert, Thomas Nelson, Bradley J. Gijs, Martin A.M. Laboratory of Microsystems LMIS2 EPFL Lausanne Switzerland Multi-Scale Robotics Lab MSRL ETH Zürich Switzerland

The Caenorhabditis elegans embryo has been extensively studied, however, its biomechanical properties are largely unknown for the time being. In this work, we performed for the first time a quantitative study of the m... 详细信息

ISBN: (纸本)9781733419000

关键词： Biomechanics

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Design and Evaluation of a Steerable Magnetic Sheath for Cardiac Ablations

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IEEE robotics and Automation Letters 2018年第3期3卷 2123-2128页

作者： Chautems, Christophe Lyttle, Sean Boehler, Quentin Nelson, Bradley J. Multi-Scale Robotics Lab ETH Zurich Zurich8092 Switzerland

Precise catheter control is crucial to the success of radiofrequency cardiac arrhythmia ablations. Remote control using external magnetic fields to directly steer the catheter tip is a promising strategy to accurately and easily perform cardiac catheter steering. Magnetic catheters must be flexible enough to be deflected by a magnetic field but rigid enough to provide sufficient force and stability during ablation. These conflicting requirements have limited the design options and effectiveness of magnetic catheters. Furthermore, the ablation force achievable by magnetic catheters depends strongly on the catheter's bending angle;at angles greater than 90°, it can be very difficult to achieve any significant force during ablation. To overcome these shortcomings, we propose to magnetically control a flexible segment at the distal tip of the introducer sheath, rather than the catheter. Control of the tip orientation is thus decoupled from catheter insertion, enabling more robust and intuitive manipulability of the catheter. Usability testing with the Aeon Phocus, a magnetic navigation system, has shown that the control of this magnetic sheath is indeed more intuitive than the control of a standard magnetic catheter. © 2016 IEEE.

关键词： Catheters

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On-Command Disassembly of Microrobotic Superstructures for Transport and Delivery of Magnetic Micromachines

arXiv

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arXiv 2023年

作者： Landers, Fabian C. Gantenbein, Valentin Hertle, Lukas Veciana, Andrea Llacer-Wintle, Joaquin Chen, Xiang-Zhong Ye, Hao Franco, Carlos Puigmartí-Luis, Josep Kim, Minsoo Nelson, Bradley J. Pané, Salvador Multi-Scale Robotics Lab Institute of Robotics and Intelligent Systems ETH Zurich Tannenstrasse 3 Zurich8092 Switzerland Institute of Optoelectronics Shanghai Frontiers Science Research Base of Intelligent Optoelectronics and Perception Fudan University Shanghai200438 China Yiwu Research Institute of Fudan University Zhejiang Yiwu322000 China Departament de Ciència dels Materials i Química Física Institut de Química Teòrica i Computacional University of Barcelona Martí i Franquès 1 Barcelona08028 Spain Pg. Lluís Companys 23 Barcelona08010 Spain

Magnetic microrobots have been developed for navigating microscale environments by means of remote magnetic fields. However, limited propulsion speeds at small scales remain an issue in the maneuverability of these devices as magnetic force and torque are proportional to their magnetic volume. Here, we propose a microrobotic superstructure, which, as analogous to a supramolecular system, consists of two or more microrobotic units that are interconnected and organized through a physical (transient) component (a polymeric frame or a thread). Our superstructures consist of microfabricated magnetic helical micromachines interlocked by a magnetic gelatin nanocomposite containing iron oxide nanoparticles (IONPs). While the microhelices enable the motion of the superstructure, the IONPs serve as heating transducers for dissolving the gelatin chassis via magnetic hyperthermia. In a practical demonstration, we showcase the superstructure’s motion with a gradient magnetic field in a large channel, the disassembly of the superstructure and release of the helical micromachines by a high-frequency alternating magnetic field, and the corkscrew locomotion of the released helices through a small channel via a rotating magnetic field. This adaptable microrobotic superstructure reacts to different magnetic inputs, which could be used to perform complex delivery procedures within intricate regions of the human body. © 2023, CC BY-NC-ND.

关键词： Iron oxides

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Powering and Fabrication of Small-scale robotics Systems

引用

Current robotics reports 2021年第4期2卷 427-440页

作者： Salvador Pané Pedro Wendel-Garcia Yonca Belce Xiang-Zhong Chen Josep Puigmartí-Luis Multi-Scale Robotics Lab (MSRL) Institute of Robotics and Intelligent Systems (IRIS) ETH Zurich CH-8092 Zurich Switzerland. Institute of Intensive Care Medicine University Hospital of Zürich Zürich Switzerland. Departament de Ciència Dels Materials I Química Física Institut de Química Teòrica I Computacional 08028 Barcelona Spain.

PURPOSE OF REVIEW:The increasing number of contributions in the field of small-scale robotics is significantly associated with the progress in material science and process engineering during the last half century. With the objective of integrating the most optimal materials for the propulsion of these motile micro- and nanosystems, several manufacturing strategies have been adopted or specifically developed. This brief review covers some recent advances in materials and fabrication of small-scale robots with a focus on the materials serving as components for their motion and actuation. RECENT FINDINGS:Integration of a wealth of materials is now possible in several micro- and nanorobotic designs owing to the advances in micro- and nanofabrication and chemical synthesis. Regarding light-driven swimmers, novel photocatalytic materials and deformable liquid crystal elastomers have been recently reported. Acoustic swimmers are also gaining attention, with several prominent examples of acoustic bubble-based 3D swimmers being recently reported. Magnetic micro- and nanorobots are increasingly investigated for their prospective use in biomedical applications. The adoption of different materials and novel fabrication strategies based on 3D printing, template-assisted electrodeposition, or electrospinning is briefly discussed. SUMMARY:A brief review on fabrication and powering of small-scale robotics is presented. First, a concise introduction to the world of small-scale robotics and their propulsion by means of magnetic fields, ultrasound, and light is provided. Recent examples of materials and fabrication methodologies for the realization of these devices follow thereafter.

关键词： Micro- and nanofabrication Micro- and nanoscale propulsion Mobile small-scale robotics

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Modeling Electromagnetic Navigation Systems for Medical Applications using Random Forests and Artificial Neural Networks

Modeling Electromagnetic Navigation Systems for Medical Appl...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Ruoxi Yu Samuel L. Charreyron Quentin Boehler Cameron Weibel Christophe Chautems Carmen C. Y. Poon Bradley J. Nelson Division of Biomedical Engineering Research The Chinese University of Hong Kong Shatin Hong Kong SAR Multi-Scale Robotics Lab ETH Zurich Zurich Switzerland

ISBN: (数字)9781728173955

ISBN: (纸本)9781728173962

Electromagnetic Navigation Systems (eMNS) can be used to control a variety of multiscale devices within the human body for remote surgery. Accurate modeling of the magnetic fields generated by the electromagnets of an eMNS is crucial for the precise control of these devices. Existing methods assume a linear behavior of these systems, leading to significant modeling errors within nonlinear regions exhibited at higher magnetic fields, preventing these systems from operating at full capacity. In this paper, we use a random forest (RF) and an artificial neural network (ANN) to model the nonlinear behavior of the magnetic fields generated by an eMNS. Both machine learning methods outperformed the state-of-the-art linear multipole electromagnet model (MPEM). The RF and the ANN model reduced the root mean squared error (RMSE) of the MPEM when predicting the field magnitude by approximately 40% and 87%, respectively, over the entire current range of the eMNS. At high current regions, especially between 30 and 35 A, the field-magnitude RMSE improvement of the ANN model over the MPEM was 37 mT, equivalent to 90% error reduction. This study demonstrates the feasibility of using machine learning to model an eMNS for medical applications, and its ability to account for complex nonlinear behavior at high currents. The use of machine learning thus shows promise in developing accurate field predicting models, and ultimately improving surgical procedures that use magnetic navigation.

关键词： Saturation magnetization Electromagnets Current measurement Magnetic cores Magnetostatics Magnetic resonance imaging Magnetic separation

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