Orthogonal Force Research Articles

Automatic shock excitation system for dynamic calibration of six-axis force/torque sensor

The coupling behavior between the six-axis force/torque (F/T) sensor and the mechanical environment introduces variations in the dynamic parameters obtained through different calibration methods and devices, which poses challenges in proposing dynamic performance criteria. This paper presents a comprehensive automatic calibration system for determining the dynamic characteristics of the six-axis F/T sensor. Impulse force generators (IFGs), positioned at various orientations, apply three mutually orthogonal directional force and torque components to the sensor using a cruciform artifact. The system ensures repeatable impulse excitation by maintaining consistent spring compression in the IFG, measured by the displacement control system's grating ruler. The pulse width and frequency response function (FRF) are determined based on the response signal without measuring the input signal. The calibration frequency and the impact force magnitude can be controlled by selecting appropriate system parameters. Compared to manual impulse hammers, IFGs exhibit superior features such as high bandwidth, repeatability, and controllable force amplitude. They provide high-quality impulse excitation with calibration frequencies and forces up to 30 kHz and 2500 N or even higher, respectively. Furthermore, a linear relationship between peak value of impulse excitation and spring compression is studied to ensure effective excitation application. The consistency of dynamic calibration results of the six-axis F/T sensor verifies the effectiveness of this automatic calibration system.

Fundamental studies on tactile feedback in robotic Striploin fat trimming task

This study explores a tactile perception approach for guiding a robotic cutting tool in beef processing. A 6-axis manipulator with a static knife and a 6-axis force sensor performed fifteen cutting paths on five striploin steak pieces. Unique force transients from the knife tip and sides were used to determine the knife's position relative to tissue features. Cross-correlation analysis between the orthogonal force components revealed a high coefficient above 0.95 for paths away from the interface, dropping below 0.88 near air gaps or fat-lean interfaces due to disturbances and tissue breakdown. Force transients were also identified when the knife exited the fat layer using a programmatic method, achieving less than a 1-s deviation from manual measurements. The lateral force component showed sensitivity to the natural cutting path and surrounding tissue behaviour. These tactile perception techniques could be integrated into real-time control for a robotic cutting knife in beef processing.

Pushing with Soft Robotic Arms via Deep Reinforcement Learning

Soft robots can adaptively interact with unstructured environments. However, nonlinear soft material properties challenge modeling and control. Learning‐based controllers that leverage efficient mechanical models are promising for solving complex interaction tasks. This article develops a closed‐loop pose/force controller for a dexterous soft manipulator enabling dynamic pushing tasks using deep reinforcement learning. Force tests investigate the mechanical properties of a soft robot module, resulting in orthogonal forces of N. Then, the policy is trained in simulation leveraging a dynamic Cosserat rod model of the soft robot. Domain randomization mitigate the sim‐to‐real gap while careful reward engineering induced pose and force control even without explicit force inputs. Despite the approximate simulation, the sim‐to‐real transfer achieved an average reaching distance of mm (), an average orientation error of rad () and applied pushing forces up to N. Such performance is reasonable for the intended assistive tasks of the manipulator. The experiments uncovered that the soft robot interacting with the environment exhibited torsional and counter‐balancing movements. Although not explicitly enforced, they emerged from the mechanical intelligence of the manipulator. The results demonstrate the potential of soft robotic manipulation via reinforcement learning.

Size and Shape Selective Classification of Nanoparticles

As nanoparticle syntheses on a large scale usually yield products with broad size and shape distributions, the properties of nanoparticle-based products need to be tuned after synthesis by narrowing the size and shape distributions or via the removal of undesired fractions. The development of property-selective classification processes requires a universal framework for the quantitative evaluation of multi-dimensional particle fractionation processes. This framework must be applicable to any property and any particle classification process. We extended the well-known one-dimensional methodology commonly used for describing particle size distributions and fractionation processes to the multi-dimensional case to account for the higher complexity of the property distribution and separation functions. In particular, multi-dimensional lognormal distributions are introduced and applied to diameter and length distributions of gold nanorods. The fractionation of nanorods via centrifugation and by orthogonal centrifugal and electric forces is modeled. Moreover, we demonstrate that analytical ultracentrifugation with a multi-wavelength detector (MWL-AUC) is a fast and very accurate method for the measurement of two-dimensional particle size distributions in suspension. The MWL-AUC method is widely applicable to any class of nanoparticles with size-, shape- or composition-dependent optical properties. In addition, we obtained distributions of the lateral diameter and the number of layers of molybdenum disulfide nanosheets via stepwise centrifugation and spectroscopic evaluation of the size fractions.

Very-long-period signal reveals lava lake sloshing and its interaction with a deep reservoir in Nyiragongo volcano

The longevity of lava lakes in open-vent volcanoes reflects a hydraulic connection between the lake and the deep part of the magma plumbing system. Constraining the size of the shallow magmatic system and resolving the rheology of magma filling in the system is essential to evaluate potential hazards like lava flow and other activities. As the lava lake is often perturbed by degassing bursts, rockfall, and even convection, seismic waves radiated from the oscillation of fluid and its mechanical coupling with the surrounding solid walls provide invaluable information on probing system geometry and magma rheology. In this report, I show the first observation of very long-period signals in Nyiragongo volcano, to uncover the sloshing of the world's largest known lava lake and its dynamic interaction with a deep reservoir during the relatively quiet period. The signal is manifested as the ground oscillations with two isolated spectral peaks at ∼15 s and ∼16 s sustaining up to half an hour and a spectral peak at a longer period of ∼76 s. The radiated seismic energy can be well recognized by the stations with distances of <50 km to the lava lake. The traveling time, particle-motion polarization, and deformation inversion suggest that the 15 s' and 16 s' modes are related to two orthogonal horizontal forces at a very shallow depth, likely pointing to the sloshing dynamics of the lava lake. The 76 s' mode is considered as the dynamic coupling between the lake bottom to a deep reservoir at a depth of 8–16 km through a conduit driven by the sloshing. The dynamic modeling of the 76 s' mode points to a deep reservoir storativity of ∼8 m3/Pa and a spherical reservoir with a radius of ∼7.5 km. High-frequency seismic waves before the onset of the 15 s' and 16 s' modes suggest that the signals may be excited by rigorous degassing or rockfall. Variations in the period and quality factor of the modes reflect the changes in the lake/reservoir geometry and magma rheology. This finding may improve our ability to understand the magmatic plumbing system, track magma evolution in Nyiragongo, and further probe the formation of lava lakes in active volcanoes.

A novel mechanical attachment for biaxial tensile test: Application to formability evaluation for DP590 at different temperatures

A novel mechanical attachment for conducting in-plane biaxial tensile test is provided in this paper. In this attachment, the conversion of force from an external actuator into two pairs of orthogonal forces is achieved by specially designed trapezoidal blocks. By using trapezoidal blocks with different inclination angles, biaxial tensile tests of six different tensile ratios can be performed. A heating device is designed for the attachment to conduct thermal biaxial tensile tests. The heating device adopts a combination of the induction heating technology and the conduction heating method. With the developed mechanical attachment and the heating device, the forming limit curves (FLC) of DP590 sheets at ambient temperature, 300 °C, 400 °C and 500 °C are determined using biaxial tensile tests. A classical Nakazima test procedure at ambient temperature is carried out to establish a reference FLC for the material, and the reference FLC is further used to evaluate the results from biaxial tensile tests. Furthermore, an anisotropic GTN model based on Yld2000-3d yield criterion is calibrated by inverse identification procedures and applied to predict the localized necking and fracture for DP590 sheets under biaxial tensions.

Engineering Nano/Microscale Chiral Self-Assembly in 3D Printed Constructs

HighlightsTo precisely engineer complex helical hierarchies at nano/microscales, reactive inks with chiral nematic anisotropy are designed for 3D printing.The phase transformations and chiral evolution in response to parallel and orthogonal shear forces are meticulously investigated to finely adjust the 3D printing parameters for programming oriented chiral assemblies.The interplay between chiral relaxation dynamics and photo-polymerization kinetics is finely tuned to enable well-controlled chiral reformation, while simultaneously ensuring high print quality.

Ultraloop: Active Lateral Force Feedback Using Resonant Traveling Waves.

The sensation of touching virtual texture and shape can be provided to a touchscreen user by varying the friction force. Despite the saliency of the sensation, this modulated frictional force is purely passive and strictly opposes finger movement. Therefore, it is only possible to create forces along the direction of movement and this technology cannot stimulate a static fingertip or provide forces that are orthogonal to the direction of movement. The lack of orthogonal force limits the guidance to a target in an arbitrary direction and there is a need for active lateral forces to give directional cues to the fingertip. Here, we introduce a surface haptic interface that uses ultrasonic traveling waves to create an active lateral force on bare fingertips. The device is built around a ring shape cavity where two degenerate resonant modes around 40 kHz are excited with 90 ° phase shift. The interface provides active forces up to 0.3 N to a static bare finger uniformly over a 140×30 mm 2 surface. We report the model and design of the acoustic cavity, force measurements, and an application to create a key-click sensation. This work demonstrates a promising method for uniformly producing large lateral forces on a touch surface.

Micro-computed tomography shows silent bubbles in squeaky mozzarella

Abstract The sound of food is of influence on how its flavour is perceived. Although rarely studied in psychoacoustics, cheese may have a resonating internal structure in the audible spectrum. It has been speculated that this structure or small bubbles that are formed as a result of fermentation are responsible for creating audible acoustic responses. The purpose of this study was to design a mechanical methodology to create audible acoustics from cheese samples and to quantify bubble presence in a sample. One hundred and two samples of mozzarella cheese with 1.5±0.4-cm3 volumes were subjected to shear from a wetted steel blade, whilst orthogonal force, blade acceleration, and acoustic response were continuously monitored. In addition, micro-computed tomography was performed. It was found that under our measurement conditions, mozzarella was forced to squeak in 10% of the experiments, at fundamental squeak frequencies up to 2 kHz, which indicates that the acoustics come from a resonating porous structure, rather than from resonating bubbles. The micro-computed tomography showed a bubble density of 51 cm−3. This low bubble density may account for the absence of a high-frequency component in the spectra analysed. Our results confirm the presence of small bubbles in squeaky mozzarella, but these generate frequencies much higher than those recorded.

Design of a Custom Force Fixture Fitting Miniature Load Cells for Individual Finger Force Measurement

This research aims to address limitations of current hand grip measurement techniques by designing, building, and testing a more robust cylindrical dynamometer capable of measuring orthogonal force components while accounting for forces exerted by individual finger segments. The novel grip fixture consists of three static beams instrumented with strain gauges measuring orthogonal forces and eight attached miniature compensating load cells accounting for force contribution from finger segments. Following device fabrication and calibration, data was validated in a pilot study (n=6) where grip strengths were compared between the custom fixture and a Jamar dynamometer. Data suggests the custom dynamometer provides hand grip strength measurement comparable to that produced on a traditional dynamometer (p &gt; 0.05). Future research studies using a similar device can guide therapy for patients with impaired hand strength by providing clinical professionals with a more complete profile of the forces exerted by hand segments.

Composite Disturbance Rejection Control Strategy for Multi-Quadrotor Transportation System

In this paper, a composite disturbance rejection control algorithm is developed for cooperatively carrying a cable-suspended payload in multi-quadrotor transportation system (MQTS). Firstly, based on the Newton Euler's method and orthogonal force decomposition, a precise MQTS model is established which takes a general rigid body payload into account. Then, a multi-loop control strategy is designed to deal with the coupled states and underactuation in MQTS, where the payload is expected to move along a desired trajectory. Furthermore, the disturbance observer (DOB) is introduced, and the disturbance estimation is incorporated in controller to actively compensate the effect of external disturbance in different control loop. Finally, the effectiveness of the proposed method is validated by simulation results.

Self-Assembled Tetratic Crystals by Orthogonal Colloidal Force.

Bonding simple building blocks to create crystalline materials with design has been sophisticated in the molecular world, but this is still very challenging for anisotropic nanoparticles or colloids, because the particle arrangements, including position and orientation, cannot be manipulated as expected. Here biconcave polystyrene (PS) discs to present a shape self-recognition route are used, which can control both the position and orientation of particles during self-assembly by directional colloidal forces. An unusual but very challenging two-dimensional(2D) open superstructure-tetratic crystal (TC)-is achieved. The optical properties of the 2D TCs are studied by the finite difference time domain method, showing that the PS/Ag binary TC can be used to modulate the polarization state of the incident light, for example, converting the linearly polarized light into left-handed or right-handed circularly polarized light. This work paves an important way for self-assembling many unprecedented crystalline materials.

Performance analysis of over-constrained orthogonal parallel six-axis force sensor

An over-constrained orthogonal parallel six-axis force sensor is an improvement over the traditional parallel six-axis force sensor and has the advantage of simple mapping relations. According to this improved configuration, performance parameters, such as decoupling characteristics, uniform-load characteristics, and range-limited characteristics, were used for performance analysis and were mathematically established. Then, the relation between the performance parameters and sensor design parameters was analysed numerically. Finally, a sensor prototype was designed and optimised into a second prototype based on the analysis of performance parameters. Results show that the vertical branch decoupling characteristic of the first and second prototypes were 19 % and 8.8 % full-scale (FS), respectively, and the range-limited characteristics of the first and second prototypes are 7.1 % in the Fz direction and 3.9 % FS, respectively. This shows that the proposed performance parameters can better analyse the performance of the over-constrained orthogonal parallel six-axis force sensor and optimise the sensor structure.

Assessment of open surgery suturing skill: Simulator platform, force-based, and motion-based metrics.

ObjectiveThis paper focuses on simulator-based assessment of open surgery suturing skill. We introduce a new surgical simulator designed to collect synchronized force, motion, video and touch data during a radial suturing task adapted from the Fundamentals of Vascular Surgery (FVS) skill assessment. The synchronized data is analyzed to extract objective metrics for suturing skill assessment.MethodsThe simulator has a camera positioned underneath the suturing membrane, enabling visual tracking of the needle during suturing. Needle tracking data enables extraction of meaningful metrics related to both the process and the product of the suturing task. To better simulate surgical conditions, the height of the system and the depth of the membrane are both adjustable. Metrics for assessment of suturing skill based on force/torque, motion, and physical contact are presented. Experimental data are presented from a study comparing attending surgeons and surgery residents.ResultsAnalysis shows force metrics (absolute maximum force/torque in z-direction), motion metrics (yaw, pitch, roll), physical contact metric, and image-enabled force metrics (orthogonal and tangential forces) are found to be statistically significant in differentiating suturing skill between attendings and residents.Conclusion and significanceThe results suggest that this simulator and accompanying metrics could serve as a useful tool for assessing and teaching open surgery suturing skill.

Optofluidic Particle Manipulation: Optical Trapping in a Thin-Membrane Microchannel.

We demonstrate an optofluidic device which utilizes the optical scattering and gradient forces for particle trapping in microchannels featuring 300 nm thick membranes. On-chip waveguides are used to direct light into microfluidic trapping channels. Radiation pressure is used to push particles into a protrusion cavity, isolating the particles from liquid flow. Two different designs are presented: the first exclusively uses the optical scattering force for particle manipulation, and the second uses both scattering and gradient forces. Trapping performance is modeled for both cases. The first design, referred to as the orthogonal force design, is shown to have a 80% capture efficiency under typical operating conditions. The second design, referred to as the gradient force design, is shown to have 98% efficiency under the same conditions.

Study on Impact Test System of Manipulator Based on Six Axis Force Sensor and Intelligent Controller

With the development and application of intelligent nervous system, intelligent control system represented by machine vision has been promoted and used in various fields, including manipulator control system. Mechanical arm is the main actuator of robot and other mechanical components, but the application environment of mechanical arm is extremely complex, and with the development of industrial process, the sensitivity of technology and operating system for its arbitrary posture operation is also steadily improved. Based on the above problems, this paper designs a manipulator control system based on machine vision theory and orthogonal parallel six-dimensional force sensor to meet the working requirements of manipulator in high-precision environment. Systems hardware are consisted by machine vision structure and six dimensions of force sensor. The practical application effect of the model was verified by collision detection experiment. The relevant research can provide theoretical guidance and practical reference for the research of manipulator control field. Dance and practical application reference for the research of manipulator control field.

Tunable interfacial adhesion based on orthogonal supramolecular forces

Orthogonal supramolecular forces were introduced into adhesive gel, and its interfacial adhesion strength could be adjusted through adding competitive molecules.

Characterizing Detection Thresholds for Six Orthogonal Modes of Vibrotactile Display Via Stylus With Precision Grasp.

In this paper, we characterize the detection thresholds in six orthogonal modes of vibrotactile haptic display via stylus, including three orthogonal force directions and three orthogonal torque directions at the haptic interaction point. A psychophysical study is performed to determine detection thresholds over the frequency range 20-250 Hz, for six distinct styluses. Analysis of variance is used to test the hypothesis that force signals, as well as torque signals, applied in different directions have different detection thresholds. We find that people are less sensitive to force signals parallel to the stylus than to those orthogonal to the stylus at low frequencies, and far more sensitive to torque signals about the stylus than to those orthogonal to the stylus. Optimization techniques are used to determine four independent two-parameter models to describe the frequency-dependent thresholds for each of the orthogonal force and torque modes for a stylus that is approximately radially symmetric; six independent models are required if the stylus is not well approximated as radially symmetric. Finally, we provide a means to estimate the model parameters given stylus parameters, for a range of styluses, and to estimate the coupling between orthogonal modes.

On learning disentangled representations for individual treatment effect estimation

ObjectiveEstimating the individualized treatment effect (ITE) from observational data is a challenging task due to selection bias, which results from the distributional discrepancy between different treatment groups caused by the dependence between features and assigned treatments. This dependence is induced by the factors related to the treatment assignment. We hypothesize that features consist of three types of latent factors: outcome-specific factors, treatment-specific factors and confounders. Then, we aim to reduce the influence of treatment-related factors, i.e., treatment-specific factors and confounders, on outcome prediction to mitigate the effects of selection bias. MethodWe present a novel representation learning model in which both the main task of outcome prediction and the auxiliary task of classifying the treatment assignment are used to learn the outcome-oriented and treatment-oriented latent representations, respectively. However, since the confounders are related to both treatment assignment and outcome, it is still contained in the representations. To further reduce influence of the confounders contained in both representations, individualized orthogonal regularization is incorporated into the proposed model. The orthogonal regularization forces the outcome-oriented and treatment-oriented latent representations of an individual to be vertical in the inner product space, meaning they are orthogonal with each other, and the common information of confounder is reduced. Such that the ITE can be estimated more precisely without the effects of selection bias. ResultWe evaluate our proposed model on a semi-simulated dataset and a real-world dataset. The experimental results demonstrate that the proposed model achieves competitive or better performance compared with the performances of the state-of-the-art models. ConclusionThe proposed method is well performed on ITE estimation with the ability to reduce selection bias thoroughly by incorporating an auxiliary task and adopting orthogonal regularization to disentangle the latent factors. Significance: This paper offers a novel method of reducing selection bias in estimating the ITE from observational data by disentangled representation learning.

A Smart Tool Holder Calibrated by Machine Learning for Measuring Cutting Force in Fine Turning and Its Application to the Specific Cutting Force of Low Carbon Steel S15C

Real-time monitoring of the cutting force in the machining process is critical for improving machining accuracy, optimizing the machining process, and optimizing tool lifetime; however, the dynamometers are too expensive to be widely used by machine tool users. Therefore, this paper presents a simple and cheap apparatus—a smart tool holder—to measure the cutting force of turning tools in the finishing turning. The apparatus does not change the structure of the turning tool. It consists of a tool holder and a piezoresistive force sensor foil, and transmits the signal through Bluetooth wireless communication. Instead of dealing with the circuit hardware, this paper uses the Artificial Neural Network (ANN) model to successfully calibrate the warm-up shift problem of the piezoresistive force sensor. Such a software method is simple, and considerably cheaper than the hardware method. For the force measurement capability of the smart tool holder, the cross-interference between orthogonal forces are very small and thus can be ignored. The force reading of the smart tool holder possesses high repeatability for the same turning parameters and high accuracy within the experiment groups. The authors apply the smart tool holder to cut the low carbon steel S15C, and to determine its specific cutting force in fine turning. The resulting fine turning force model agrees very well with the measurement. Its mean absolute deviation is 3.87% and its standard deviation is 1.55%, which reveals that the accuracy and precision of the smart tool holder and the fine turning force model are both good.