Optical fibre force sensor for minimal-invasive-surgery grasping instruments

Lazeroms, M.; Villavicencio, G.; Jongkind, W.; Honderd, G.

doi:10.1109/iembs.1996.656931

Cited by 18 publications

(19 citation statements)

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“…Tholey et al found that the required grasping and cutting forces at the jaws are approximately 3 N and 4 N, respectively [6]. Jan Peirs et al measured the force range of the tool-tip during a suturing test, and concluded that it is ±2.5N, while Lazeroms et al suggested the force range of ±10N [7]. In this paper, the grasping force requirement of 4 N and the tool-tip force requirement of 10 N are used.…”

Section: A Requirementsmentioning

confidence: 99%

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Design of a compact 5-DOF surgical robot of a spherical mechanism: CURES

Kim

Shin

et al. 2008

2008 IEEE/ASME International Conference on Advanced Intelligent Mechatronics

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In recent years, several surgical or assistant robots have made a successful debut to surgical theatre. Due to their large size, and high price, there is a growing need for the miniaturization of these surgical robots. In this paper, a design methodology for a compact surgical robot is presented. Considering workspace and force requirements, a simulation and experiments are conducted to determine the design parameters. The compact surgical robot CURES of 5-DOF spherical mechanism is developed from the analysis and its properties are presented.

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Section: A Requirementsmentioning

confidence: 99%

“…In the analysis, gravitational force and external forces are considered. As stated earlier, the force requirement of the tool-tip is set as ±10 N [7]. External forces are applied at the tool-tip in 26 different directions which are linear combination of elementary direction vectors, i.e.…”

Section: Maximum Torque Analysis With External Forcesmentioning

confidence: 99%

Design of a compact 5-DOF surgical robot of a spherical mechanism: CURES

Kim

Shin

et al. 2008

2008 IEEE/ASME International Conference on Advanced Intelligent Mechatronics

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“…However, strain gauges are sensitive to electromagnetic noise and temperature changes, which can cause drift and hysteresis . Optical force sensors for MIS have also been developed, which are insensitive to electromagnetic noise and can offer high sensitivity for small deflections without direct temperature dependence, and no hysteresis. However, optical fibers cannot obtain small bending radii and are sensitive to light intensity changes caused by bending of the cables or misalignment .…”

Section: Introductionmentioning

confidence: 99%

External force estimation and implementation in robotically assisted minimally invasive surgery

Sang

Yun

Monfaredi

et al. 2017

Robotics Computer Surgery

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“…strain gage, capacitive) due to MRI compatibility (for fiber-based LIM sensors) and the potential to be implemented on non-metallic (flexible) robotic platforms that undergo large strains. Optoelectronic sensors have been used to sense forces ( [1,2,3]) and enable closed-loop shape estimation [4,5] of flexible surgical robots. A drawback of using optoelectronic transduction mechanisms is an inherent sensitivity to ambient conditions such as environmental irradiance and temperature, which introduce errors that arise in the form of 'false' force measurements.…”

Section: Introductionmentioning

confidence: 99%

Machine learning approaches to environmental disturbance rejection in multi-axis optoelectronic force sensors

Gafford

Doshi‐Velez

Wood

et al. 2016

Sensors and Actuators A: Physical

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Light-Intensity Modulated (LIM) force sensors are seeing increasing interest in the field of surgical robotics and flexible systems in particular. However, such sensing modalities are notoriously susceptible to ambient effects such as temperature and environmental irradiance which can register as false force readings. We explore machine learning techniques to dynamically compensate for environmental biases that plague multi-axis optoelectronic force sensors. In this work, we fabricate a multisensor: three-axis LIM force sensor with integrated temperature and ambient irradiance sensing manufactured via a monolithic, origami-inspired fabrication process called printed-circuit MEMS. We explore machine learning regression techniques to compensate for temperature and ambient light sensitivity using on-board environmental sensor data. We compare batch-based ridge regression, kernelized regression and support vector techniques to baseline ordinary least-squares estimates to show that on-board environmental monitoring can substantially improve sensor force tracking performance and output stability under variable lighting and large (>100C) thermal gradients. By augmenting the least-squares estimate with nonlinear functions describing both environmental disturbances and cross-axis coupling effects, we can reduce the error in F x , F y and F z by 10%, 33%, and 73%, respectively. We assess viability of each algorithm tested in terms of both prediction accuracy and computational overhead, and analyze kernel-based regression for prediction in the context of online force feedback and haptics applications in surgical robotics. Finally, we suggest future work for fast approximation and prediction using stochastic, sparse kernel techniques.

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Optical fibre force sensor for minimal-invasive-surgery grasping instruments

Cited by 18 publications

References 0 publications

Design of a compact 5-DOF surgical robot of a spherical mechanism: CURES

Design of a compact 5-DOF surgical robot of a spherical mechanism: CURES

External force estimation and implementation in robotically assisted minimally invasive surgery

Machine learning approaches to environmental disturbance rejection in multi-axis optoelectronic force sensors

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