The navigation of magnetic medical robots typically relies on localizing an actuated, intracorporeal, ferromagnetic body and back-computing a necessary field and gradient that would result in a desired wrench on the device. Uncertainty in this localization degrades the precision of force transmission. Reducing applied force uncertainty may enhance tasks such as navigation of miniature robots, actuation of magnetically guided catheters, tissue palpation, as well as simply ensuring a bound on forces applied on sensitive tissue. In this paper, we analyzed the effects of localization noise on force uncertainty by using sensitivity ellipsoids of the magnetic force Jacobian and introduced an algorithm for uncertainty reduction. We validated the algorithm in both a simulation study and in a physical experiment. In simulation, we observed reductions in estimated force uncertainty by factors of up to 2.8 and 3.1 when using one and two actuating magnets, respectively. On a physical platform, we demonstrated a force uncertainty reduction by a factor of up to 2.5 as measured using an external sensor. Being the first consideration of force uncertainty resulting from noisy localization, this work provides a strategy for investigators to minimize uncertainty in magnetic force transmission.
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http://dx.doi.org/10.1109/TRO.2019.2917817 | DOI Listing |
Sci Rep
January 2025
Automotive Business School, Hubei University of Automotive Technology, Shiyan, 442000, Hubei, China.
In the current complex economic environment, entrepreneurial enterprises, as a crucial force in China's economic transformation, have vital survival and development strategies. This study is grounded in resource-based theory, integrating strategic management and contingency theories. It establishes a theoretical model based on the influence pathway of "entrepreneurial orientation-market orientation-entrepreneurial performance", incorporating environmental uncertainty as a moderating variable.
View Article and Find Full Text PDFData Brief
February 2025
Institut Camille Jordan, UMR-CNRS 5208, École Centrale de Lyon, 36 Avenue Guy de Collongue, 69134, Écully, France.
The dataset presented contains the experimental structural response, in the frequency domain, of a suspended steel plate to a point force excitation. The plate is excited by a mechanical point force generated by a Brüel & kJær shaker with a white noise signal input from 3.125 Hz to 2000 Hz.
View Article and Find Full Text PDFJ Theor Biol
January 2025
Department of Biology, University of Maryland, College Park, 20742, MD, USA; Institut de Biologie, Ecole Normale Superieure, Paris, 75005, France; School of Biological Sciences, Georgia Institute of Technology, Atlanta, 30332, GA, USA. Electronic address:
Virus population dynamics are driven by counter-balancing forces of production and loss. Whereas viral production arises from complex interactions with susceptible hosts, the loss of infectious virus particles is often approximated as a first-order kinetic process. As such, experimental protocols to measure infectious virus loss are not typically designed to identify non-exponential decay processes.
View Article and Find Full Text PDFSensors (Basel)
December 2024
Xi'an Institute of Optics and Precision Mechanics of CAS, Xi'an 710119, China.
During the interaction process of a manipulator executing a grasping task, to ensure no damage to the object, accurate force and position control of the manipulator's end-effector must be concurrently implemented. To address the computationally intensive nature of current hybrid force/position control methods, a variable-parameter impedance control method for manipulators, utilizing a gradient descent method and Radial Basis Function Neural Network (RBFNN), is proposed. This method employs a position-based impedance control structure that integrates iterative learning control principles with a gradient descent method to dynamically adjust impedance parameters.
View Article and Find Full Text PDFSci Total Environ
January 2025
Center for Environmental Radioactivity (CERAD) CoE, Norwegian University of Life Sciences, P.O. Box 5003, N-1432 Ås, Norway; Faculty of Environmental Sciences and Natural Resource Management, Norwegian University of Life Sciences (NMBU), P.O.Box 5003, NO-1432 Ås, Norway.
Numerical transport models are important tools for nuclear emergency decision makers in that they rapidly provide early predictions of dispersion of released radionuclides, which is key information to determine adequate emergency protective measures. They can also help us understand and describe environmental processes and can give a comprehensive assessment of transport and transfer of radionuclides in the environment. Transport of radionuclides in air and ocean is affected by a number of different physico-chemical processes.
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