David G. Black;Amir Hossein Hadi Hosseinabadi;Nicholas Rangga Pradnyawira;Mika Nogami;Septimu E. Salcudean
{"title":"Low-Profile 6-Axis Differential Magnetic Force/Torque Sensing","authors":"David G. Black;Amir Hossein Hadi Hosseinabadi;Nicholas Rangga Pradnyawira;Mika Nogami;Septimu E. Salcudean","doi":"10.1109/TMRB.2024.3407350","DOIUrl":null,"url":null,"abstract":"Force/torque sensing on hand-held tools enables control of applied forces, which is often essential in both tele-robotics and remote guidance of people. However, existing force sensors are either bulky, complex, or have insufficient load rating. This paper presents a novel 6 axis force-torque sensor based on differential magnetic field readings in a collection of low-profile sensor modules placed around a tool or device. The instrumentation is easy to install but nonetheless achieves good performance. A detailed mathematical model and optimization-based design procedure are also introduced. The modeling, simulation, and optimization of the force sensor are described and then used in the electrical and mechanical design and integration of the sensor into an ultrasound probe. Through a neural network-based nonlinear calibration, the sensor achieves average root-mean-square test errors of 0.41 N and 0.027 Nm compared to an off-the-shelf ATI Nano25 sensor, which are 0.80% and 1.16% of the full-scale range respectively. The sensor has an average noise power spectral density of less than 0.0001 N/\n<inline-formula> <tex-math>$\\sqrt {\\text {Hz}}$ </tex-math></inline-formula>\n, and a 95% confidence interval resolution of 0.0086 N and 0.063 Nmm. The practical readout rate is 1.3 kHz over USB serial and it can also operate over Bluetooth or Wi-Fi. This sensor can enable instrumentation of manual tools to improve the performance and transparency of teleoperated or autonomous systems.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"6 3","pages":"992-1003"},"PeriodicalIF":3.4000,"publicationDate":"2024-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE transactions on medical robotics and bionics","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/10542375/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, BIOMEDICAL","Score":null,"Total":0}
引用次数: 0
Abstract
Force/torque sensing on hand-held tools enables control of applied forces, which is often essential in both tele-robotics and remote guidance of people. However, existing force sensors are either bulky, complex, or have insufficient load rating. This paper presents a novel 6 axis force-torque sensor based on differential magnetic field readings in a collection of low-profile sensor modules placed around a tool or device. The instrumentation is easy to install but nonetheless achieves good performance. A detailed mathematical model and optimization-based design procedure are also introduced. The modeling, simulation, and optimization of the force sensor are described and then used in the electrical and mechanical design and integration of the sensor into an ultrasound probe. Through a neural network-based nonlinear calibration, the sensor achieves average root-mean-square test errors of 0.41 N and 0.027 Nm compared to an off-the-shelf ATI Nano25 sensor, which are 0.80% and 1.16% of the full-scale range respectively. The sensor has an average noise power spectral density of less than 0.0001 N/
$\sqrt {\text {Hz}}$
, and a 95% confidence interval resolution of 0.0086 N and 0.063 Nmm. The practical readout rate is 1.3 kHz over USB serial and it can also operate over Bluetooth or Wi-Fi. This sensor can enable instrumentation of manual tools to improve the performance and transparency of teleoperated or autonomous systems.