Contact Detection Research Articles

Tactile Sensor with High-Density Microcantilever and Multiple PDMS Bumps for Contact Detection

In the study, we investigated a detection method of partial contact of an object owing to curved or uneven surface of the contact object by a tactile sensor. The sensor is developed using three microcantilevers embedded in a polydimethylsiloxane (PDMS) bump. First, three bumps were employed to place a bump for each cantilever. It was possible to detect a contact position because the resistance change in the strain gauge on the cantilever under each bump significantly depended on the contact/non-contact state of each bump. Second, a tactile sensor with high-density arrangement of microcantilevers was used to detect partial or tilted contact situations. The results indicated that the output of a tactile sensor with high-density arrangement of microcantilevers reflected partial or tilted contact. It is suggested that a tactile sensor with multiple bumps and high-density microcantilevers allows for more dexterous gripping control based on the shape of the object and contact angle.

Robust shape estimation with false-positive contact detection

We propose a means of omni-directional contact detection using accelerometers instead of tactile sensors for object shape estimation using touch. Unlike tactile sensors, our contact-based detection method tends to induce a degree of uncertainty with false-positive contact data because the sensors may react not only to actual contact but also to the unstable behavior of the robot. Therefore, it is crucial to consider a robust shape estimation method capable of handling such false-positive contact data. To realize this, we introduce the concept of heteroscedasticity into the contact data and propose a robust shape estimation algorithm based on Gaussian process implicit surfaces (GPIS). We confirmed that our algorithm not only reduces shape estimation errors caused by false-positive contact data but also distinguishes false-positive contact data more clearly than the GPIS through simulations and actual experiments using a quadcopter.

How Far Are We From Quantifying Visual Attention in Mobile HCI?

With an ever-increasing number of mobile devices competing for our attention, quantifying when, how often, or for how long users visually attend to their devices has emerged as a core challenge in mobile human-computer interaction. Encouraged by recent advances in automatic eye contact detection using machine learning and device-integrated cameras, we provide a fundamental investigation into the feasibility of quantifying visual attention during everyday mobile interactions. We identify core challenges and sources of errors associated with sensing attention on mobile devices in the wild, including the impact of face and eye visibility, the importance of robust head pose estimation, and the need for accurate gaze estimation. Based on this analysis, we propose future research directions and discuss how eye contact detection represents the foundation for exciting new applications towards next-generation pervasive attentive user interfaces.

Deconstructing eye contact perception: Measuring perceptual precision and self-referential tendency using an online psychophysical eye contact detection task.

Eye contact perception—the ability to accurately and efficiently discriminate others’ gaze directions—is critical to understanding others and functioning in a complex social world. Previous research shows that it is affected in multiple neuropsychiatric disorders accompanied by social dysfunction, and understanding the cognitive processes giving rise to eye contact perception would help advance mechanistic investigations of psychopathology. This study aims to validate an online, psychophysical eye contact detection task through which two constituent cognitive components of eye contact perception (perceptual precision and self-referential tendency) can be derived. Data collected from a large online sample showed excellent test-retest reliability for self-referential tendency and moderate reliability for perceptual precision. Convergence validity was supported by correlations with social cognitive measures tapping into different aspects of understanding others. Hierarchical regression analyses revealed that perceptual precision and self-referential tendency explained unique variance in social cognition, suggesting that they measure unique aspects of related constructs. Overall, this study provided support for the reliability and validity of the eye contact perception metrics derived using the online Eye Contact Detection Task. The value of the task for future psychopathology research was discussed.

Energy-tracking impulse method for particle-discretized rigid-body simulations with frictional contact

Simulations of multi-body dynamics for computer graphics, 3D game engines, or engineering simulations often involve contact and articulated connections to produce plausible results. Multi-body dynamics simulations generally require accurate contact detection and induce high computational costs because of tiny time increments. As higher accuracy and robustness are continually being sought for engineering purposes, we propose an improved multi-body dynamics simulator based on an impulse method, specifically an energy-tracking impulse (ETI) algorithm that has been modified to handle particle-discretized rigid-body simulations. In order to decrease the computational costs of the simulations, in the current work, we assume a fixed moderate time increment, allowing multiple-point contacts within a single time increment. In addition to that, we distinguish the treatment between point-to-point and multiple-point contacts, which include edge-to-surface and surface-to-surface contacts, through an additional sub-cycling iterations. The improved ETI method was verified with analytical solutions of examples with single-body contact, a frictional slip, and a rolling contact. Moreover, the method was also validated with an experimental test of a line of dominoes with multiple-point contacts. Finally, a demonstration simulation with bodies of complicated shape subjected to a large number of constraints is given to show the optimum performance of the formulation.

Visual Servo-Collision Avoidance Hybrid Task by Considering Detection and Localization of Contact for a Soft Manipulator

Due to the features of soft material, such as softness, deformability, and adaptability to constrained surroundings, soft manipulators can collide with external objects to some extent. To take the best advantage of this merit, this article presents a method of visual servo considering collisions with obstacles for a soft manipulator. First of all, a collision detection algorithm is proposed using shape feedbacks obtained by a sensor network, on the basis of the assumption that the manipulator can be considered as a combination of a static segment and a dynamic segment. Then, a contact localization algorithm is proposed to pinpoint the position where the collision occurs by minimizing the differences between the theoretical and actual shapes. An obstacle get-away algorithm, which is achieved by driving the calculated contact point to a desired position, is presented to avoid the obstacle. Along with the visual servo, a controller taking the obstacle avoidance into account is proposed to perform the hybrid task, with its stability validated via Lyaponov criterion. Finally, simulations and physical experiments are carried out to evaluate the algorithms. It is shown that the pixel error can converge to zero and the distance from the obstacle with respect to the contact point increases obviously in a short time.

Damage localization in piezo-ceramic using ultrasonic waves excited by dual point contact excitation and detection scheme

A novel experimental technique based on point contact and Coulomb coupling is devised and optimized for ultrasonic imaging of bulk and guided waves propagation in piezo-ceramics. The Coulomb coupling technique exploits the coupling and transfer of electric field to mechanical vibrations by excitation of phonons. The point contact excitation and detection technique facilitates the spatial-temporal imaging of ultrasonic waves. The motivation of this research is the diagnosis and localization of surface cracks in the piezoelectric sensors and actuators. The underlying principle of the detection scheme is that any discontinuity on the surface causes high localization of electric gradient. The localized electric field at the defect boundaries enables then to behave as secondary passive ultrasonic sources resulting in strong back reflections. However, due to the interference between transmitted and reflected wave components from rigid boundaries and defect, the resolution on the localization of the damage is challenging. Therefore, an algorithm based on the two-dimensional spectral decomposition is utilized for selective suppression of the transmitted wave. The algorithm includes data transformation and vectorization in polar coordinates for efficient spectral decomposition. In the spectral domain, the complex wave component (phase and amplitude) are suppressed for the transmitted wave field. The reflected wave component in the spectral domain is retained and retrieved back using inverse spectral transformation. The algorithm is successful in retaining and exemplifying only the reflected wave sources arising from the strong scattering of ultrasonic waves from the surface and sub-surface defects. In summary, a novel experimental technique based on Coulomb coupling and spectral decomposition technique has been implemented for localization of surface defect in piezo-ceramic structures.

Drift-Free Foot Orientation Estimation in Running Using Wearable IMU.

This study aimed to introduce and validate a new method to estimate and correct the orientation drift measured from foot-worn inertial sensors. A modified strap-down integration (MSDI) was proposed to decrease the orientation drift, which, in turn, was further compensated by estimation of the joint center acceleration (JCA) of a two-segment model of the foot. This method was designed to fit the different foot strike patterns observed in running and was validated against an optical motion-tracking system during level treadmill running at 8, 12, and 16 km/h. The sagittal and frontal plane angles obtained from the inertial sensors and the motion tracking system were compared at different moments of the ground contact phase. The results obtained from 26 runners showed that the foot orientation at mean stance was estimated with an accuracy (inter-trial median ± IQR) of 0.4 ± 3.8° and a precision (inter-trial precision median ± IQR) of 3.0 ± 1.8°. The orientation of the foot shortly before initial contact (IC) was estimated with an accuracy of 2.0 ± 5.9° and a precision of 1.6 ± 1.1°; which is more accurate than commonly used zero-velocity update methods derived from gait analysis and not explicitly designed for running. Finally, the study presented the effect initial and terminal contact (TC) detection errors have on the orientation parameters reported.

A three-dimensional approach for contact detection between realistic wheel and rail surfaces for improved railway dynamic analysis

The wheel-rail contact modeling problem assumes a preponderant role on the dynamic analysis of railway systems using multibody systems formulations. The accurate and efficient evaluation of both location and magnitude of the wheel-rail contact forces is fundamental for the development of reliable computational tools. The wheel concave zone might be a source of numerical difficulties when searching the contact points, which has been neglected in several works. Here, it is demonstrated that the minimum distance method does not always converge when the wheel surface is not fully convex, being an alternative methodology proposed to perform the contact detection. This approach examines independently the contact between each wheel strip and the rail, where the maximum virtual penetration is determined and associated with the location of the contact point. Then, an Hertzian-based force model is considered for both normal and tangential forces. The results obtained from dynamic simulations show that the minimum distance method and the proposed methodology provide a similar response for simplified wheel profiles. However, the new approach described here is reliable in the identification of the contact point when realistic wheel profiles are considered, which is not the case with the minimum distance method.

Fourier series-based discrete element method for computational mechanics of irregular-shaped particles

Many natural and engineered granular materials consist mainly of irregular-shaped non-spherical particles. In this work, a novel Fourier series-based Discrete Element Method (FS-DEM) is developed for the computational mechanics of irregular-shaped particles. In FS-DEM, Fourier series-based particle geometric description and coordinate representation are introduced, where particle shapes are implicitly determined by FS coefficients, which remain constant and are independent of particle positions or kinematics. Using the FS-based particle representation, contact detection and resolution algorithms are then developed to identify contacts and resolve contact geometric features. The FS-DEM method is completed with recourse to conventional contact behavior, laws of motion, and movement integration. The accuracy and computational efficiency of the FS-DEM framework are evaluated via three numerical examples and compared with the Overlapping Discrete Element Cluster-based DEM method. Results demonstrate the robust and superior performance of the FS-DEM method and its potential for efficient computational modeling of irregular-shaped particle systems.

Flexible, Large‐Area Covert Polarization Display Based on Ultrathin Lossy Nanocolumns on a Metal Film

AbstractCovert polarization displays provide a barrier to the inadvertent viewing of stored optical information. For security and anti‐counterfeiting purposes, access to concealed information without compromising packaging aesthetics is required in certain situations. However, optical conversion with polarized light typically requires sophisticated nanostructures only possible with limited materials, which are not appropriate for application to objects requiring flexibility or conformability, and color selectivity. A flexible, large‐area covert polarization display based on ultrathin lossy nanocolumns with wide color selectivity is presented. Self‐aligned porous nanocolumns (PNCs) fabricated by glancing angle deposition are a facile approach to polarization distinguishable structures. PNCs deposited on metal are designed to switch color in accordance with polarization by ultrathin resonance, which is modeled using the complex effective refractive index. Several combinations of material and thickness are presented to extend color selectivity with the standard red green blue gamut and color palette. As a demonstration, covert polarization display labels are attached to daily objects with curved and wrinkled surfaces, and hidden quick response codes are revealed by polarization adjustment in indoor and outdoor environments. Moreover, a multifunctional water contact detection covert polarization display is demonstrated based on the sensitivity of PNCs to the refractive index of the analyte.

Transient gear contact simulations using a floating frame of reference approach and higher-order ansatz functions

Gear drives are crucial components for a wide range of devices such as combustion engines and wind turbines. Predictions of durability, transmission errors, and noise emission are required already during early development. To that end, deformations, velocities, stresses, and contact forces can be analyzed using numerical simulations. For this, finite element analyses (FEA) or multibody system (MBS) simulations can be used. Yet, rigid MBS can be inaccurate since contact forces must be estimated using a heuristic force–displacement law since no deformations are available. Also, the need for elaborate manual tuning of contact parameters is a drawback. FEA, on the other hand, bring about long computation times that make them inappropriate for the analysis of transient phenomena. Further, a bottleneck of FEA for gears is the expensive human labor that is necessary to generate hexahedral meshes required for contact detection. Both quadratically and linearly interpolating tetrahedral meshes can be generated quickly and reliably. Tet4 elements, however, are not a viable option due to their inferior performance. Thus, as a remedy to (i) the parametrization issues and the inaccuracy inherent while using rigid MBS descriptions, (ii) the long simulation times of FEA, and (iii) the issue of expensive manual generation of hexahedral meshes, we propose using elastic multibody systems with quadratic tetrahedral meshes for dynamic contact simulations. The novelty of this contribution is the use of quadratic ansatz functions for the description of both geometry and contact calculation in combination with a floating frame of reference formulation and model order reduction.

An Optimal Electrical Impedance Tomography Drive Pattern for Human-Computer Interaction Applications.

In this article, we presented an optimal Electrical Impedance Tomography (EIT) drive pattern based on feature selection and model explanation, and proposed a portable EIT system for applications in human-computer interaction for gesture recognition and contact detection, which can reduce the measurement time and realize a performance trade-off between the accuracy and the time response. In our experiment, eleven hand gestures were designed to verify the proposed approach and EIT system. Compared to the traditional eight-electrode method, the optimal electrode drive pattern achieved a recognition accuracy of 97.5% with seven electrodes and the measurement time was reduced by 60%. To illustrate the universality of this method, we performed a contact detection experiment. By setting seven labels on the conductive panel and using optimal electrode drive pattern, the detection accuracy reached 100% with seven electrodes and the measurement time was reduced by 85%.

Image Augmentation for Eye Contact Detection Based on Combination of Pre-trained Alex-Net CNN and SVM

Image Augmentation for Eye Contact Detection Based on Combination of Pre-trained Alex-Net CNN and SVM

Hybrid Control Scheme for Grasping a Non-Cooperative Tumbling Satellite

Grasping a non-cooperative “customer satellite” with a robotic arm is a challenging task for on-orbit services of spacecraft since the collision between the robot and the target is inevitable and the dynamic behaviors of the two objects are hard to control after the collision. To grasp successfully, the contact between the space robot and the target is hoped to be maintained after the collision. In this paper, the contact control problem for grasping a non-cooperative satellite is studied. First, to simulate the contact conditions as realistic as possible, the multibody dynamics, the modified Hertz contact, and the contact detection theory are employed to establish a grasping dynamics model. Then, based on the study on the dynamic behavior of the two-ball collision problem, a hybrid control scheme with damping and attitude tracking controllers is proposed. By this scheme, the control goal, i.e. maintaining the contact between the robot and the target, can be realized after multiple collisions. Finally, numerical simulations are performed to validate the proposed control scheme, and the results demonstrate its effectiveness in grasping a non-cooperative tumbling satellite.

Evaluating Contact Detection, Size Recognization and Grasping State of an Object using Soft Elastomer Gripper

Evaluating Contact Detection, Size Recognization and Grasping State of an Object using Soft Elastomer Gripper

Fast, flexible particle simulations — An introduction to MercuryDPM

We introduce the open-source package MercuryDPM, which we have been developing over the last few years. MercuryDPM is a code for discrete particle simulations. It simulates the motion of particles by applying forces and torques that stem either from external body forces, (gravity, magnetic fields, etc.) or particle interactions. The code has been developed extensively for granular applications, and in this case these are typically (elastic, plastic, viscous, frictional) contact forces or (adhesive) short-range forces. However, it could be adapted to include long-range (molecular, self-gravity) interactions as well.MercuryDPM is an object-oriented algorithm with an easy-to-use user interface and a flexible core, allowing developers to quickly add new features. It is parallelised using MPI and released under the BSD 3-clause licence. Its open-source developers’ community has developed many features, including moving and curved walls; state-of-the-art granular contact models; specialised classes for common geometries; non-spherical particles; general interfaces; restarting; visualisation; a large self-test suite; extensive documentation; and numerous tutorials and demos. In addition, MercuryDPM has three major components that were originally invented and developed by its team: an advanced contact detection method, which allows for the first time large simulations with wide size distributions; curved (non-triangulated) walls; and multicomponent, spatial and temporal coarse-graining, a novel way to extract continuum fields from discrete particle systems. We illustrate these tools and a selection of other MercuryDPM features via various applications, including size-driven segregation down inclined planes, rotating drums, and dosing silos. Program summaryProgram Title: MercuryDPMProgram Files doi: http://dx.doi.org/10.17632/n7jmdrdc52.1Licensing provisions: BSD 3-ClauseProgramming language: C++, FortranSupplementary material: http://mercurydpm.orgNature of problem: Simulation of granular materials, i.e. conglomerations of discrete, macroscopic particles. The interaction between individual grains is characterised by a loss of energy, making the behaviour of granular materials distinct from atomistic materials, i.e. solids, liquids and gases.Solution method: MercuryDPM (Thornton et al., 2013, 2019; Weinhart et al., 2016, 2017, 2019) is an implementation of the Discrete Particle Method (DPM), also known as the Discrete Element Method (DEM) (Cundall and Strack, 1979). It simulates the motion of individual particles by applying forces and torques that stem either from external forces (gravity, magnetic fields, etc.) or from particle-pair and particle–wall interactions (typically elastic, plastic, dissipative, frictional, and adhesive contact forces). DPM simulations have been successfully used to understand the many unique granular phenomena – sudden phase transitions, jamming, force localisation, etc. – that cannot be explained without considering the granular microstructure.Unusual features: MercuryDPM was designed ab initio with the aim of allowing the simulation of realistic geometries and materials found in industrial and geotechnical applications. It thus contains several bespoke features invented by the MercuryDPM team: (i) a neighbourhood detection algorithm (Krijgsman et al., 2014) that can efficiently simulate highly polydisperse packings, which are common in industry; (ii) curved walls (Weinhart et al., 2016) making it possible to model real industrial geometries exactly, without triangulation errors; and (iii) MercuryCG (Weinhart et al., 2012, 2013, 2016; Tunuguntla et al., 2016), a state-of-the-art analysis tool that extracts local continuum fields, providing accurate analytical/rheological information often not available from experiments or pilot plants. It further contains a large range of contact models to simulate complex interactions such as elasto-plastic deformation (Luding, 2008), sintering (Fuchs et al., 2017), melting (Weinhart et al., 2019), breaking, wet and dry cohesion (Roy et al., 2016, 2017), and liquid migration (Roy et al., 2018), all of which have important industrial applications.

Reliable Activation of an EPM-Based Clinging Device for Aerial Inspection Robots

This study aims to develop a clinging device for structural inspection robots, which are expected to be used to reduce the cost of inspection of aging civil infrastructure and industrial structures. In a previous study, an electro-permanent magnet (EPM)-based clinging device that could electrically turn on and off the magnetic adhesive force against steel structures was proposed. In this study, a more versatile design of the clinging device was firstly presented, and a considerable difficulty regarding the activation process of the EPM which might impair the reliability of the clinging device was stated based on mathematical modeling and experiments. The concept of a two-step activation process was then presented to overcome the stated difficulty, and its implementation using a limit switch-based contact sensor was successfully demonstrated through collision tests. Furthermore, sensorless realization of contact detection by measuring the induced voltage across the coil of the EPM was proposed, and its feasibility was validated.

Parallelized combined finite‐discrete element (FDEM) procedure using multi‐GPU with CUDA

SummaryThis paper focuses on the efficiency of finite discrete element method (FDEM) algorithmic procedures in massive computers and analyzes the time‐consuming part of contact detection and interaction computations in the numerical solution. A detailed operable GPU parallel procedure was designed for the element node force calculation, contact detection, and contact interaction with thread allocation and data access based on the CUDA computing. The emphasis is on the parallel optimization of time‐consuming contact detection based on load balance and GPU architecture. A CUDA FDEM parallel program was developed with the overall speedup ratio over 53 times after the fracture from the efficiency and fidelity performance test of models of in situ stress, UCS, and BD simulations in Intel i7‐7700K CPU and the NVIDIA TITAN Z GPU. The CUDA FDEM parallel computing improves the computational efficiency significantly compared with the CPU‐based ones with the same reliability, providing conditions for achieving larger‐scale simulations of fracture.

Design and experiments on an inflatable link robot with a built-in vision sensor

Soft robots and manipulators with inflatable links possess inherent safety characteristics that make them a very interesting choice for tasks requiring human-robot interaction. However, they may face important challenges in their performance due to low structural stiffness. Accurate positioning of the end effector may prove a difficult task due to limitations in gravity compensation, or due to the occurrence of oscillations during motion, especially in the absence of precise information about the payload that is being manipulated. In this paper a novel approach to the design and control of a robot with an inflatable link is proposed, where the link assumes the triple role of compliant structural element, touch sensor, and active mechanism to adjust the performance of vibration control algorithms. For this, a vision sensor is placed inside the link to provide information about the structural deformation. The sensor is used to measure the tip displacement, and also to detect contact of the link surface with the surrounding environment. The concept was implemented on a two-joint rigid manipulator with a single inflatable link. Experiments on vibration control and contact detection of the inflatable link are reported where the control system was able to significantly reduce tip oscillations, including when a payload was added to the tip. The robot was also able to make binary detection of contact between the inflatable link and the user, and change its operation mode accordingly.