Contact Detection Research Articles

電気粘着ゲルシートによる固定時の電気抵抗特性

In this study, Electro-Adhesive Gel Sheet (EAGS) was fabricated. It is suggested that the electrical resistance characteristics of EAGS could be applied as slip detection sensors or contact detection sensors. EAG is a functional elastomer which can change surface adhesiveness depending on an electric field, and EAGS is a sheet of EAG fabricated on a flexible electrode sheet. It was found that slipping on the surface when grasping an object or contact with a grounded conductor changes the resistance inside the EAGS, and the mechanism was analyzed from an engineering point of view.

Novel direct simulation Monte Carlo method for spherocylinders

Traditional discrete element models of granular flows for non-spherical particles can be limited by costly contact detection. The aim of the current work is develop the foundation towards a more computationally efficient method to solve flows with non-spherical particles. This study investigates extending the direct simulation Monte Carlo, or DSMC, method to the rotational relaxation of spherocylinders. While rotational energies have been accounted for in gases within DSMC, similar models for non-spherical particles are unavailable. We propose a modified DSMC method that samples from post-collisional energies and scattering distributions derived from deterministic discrete element models. We demonstrate how to integrate derived distributions into an adapted DSMC method for spherocylinders. To assess the fidelity of the model, we consider the case of the rotational relaxing dilute gas. While the study considers spherocylinders, the methodology itself may be generalized to more complex particle shapes.

Quay Contact Detection for Ships using Motion Sensors and Machine Learning

Detecting when and where contact with the quay appears is an important ability for ships undergoing a docking maneuver. The motion of the quay, environmental forces, and hydrodynamic effects caused by the interaction between the ship and the quay are all important factors that affect if a docking procedure succeeds or not. This paper studies how contact with the quay can be detected using conventional motion sensors. This includes sensor data from inertial measurement units, global navigation satellite systems, and estimates from an inertial navigation system. The contact detection task can be interpreted as a binary classification problem deciding if contact has occurred or not. Three conventional supervised machine learning methods are studied using experimental data captured in full-scale experiments. Logistic regression, a support vector machine and a long-term short memory network have been trained and investigated. The results are promising and a proof of concept illustrating that supervised machine learning is a viable strategy for quay contact detection using motion sensors.

Detection of Forceps Contact to Retinal Model by Using Digital Image Correlation for Eye Surgical Simulator

Detection of Forceps Contact to Retinal Model by Using Digital Image Correlation for Eye Surgical Simulator

Influence of intermolecular interactions on the infrared complex indices of refraction for binary liquid mixtures.

This paper investigates the accuracy of deriving the composite optical constants of binary mixtures from only the complex indices of refraction of the neat materials. These optical constants enable the reflectance spectra of the binary mixtures to be modeled for multiple scenarios (e.g., different substrates, thicknesses, volume ratios), which is important for contact and standoff chemical detection. Using volume fractions, each mixture's complex index of refraction was approximated via three different mixing rules. To explore the impact of intermolecular interactions, these predictions are tested by experimental measurements for two representative sets of binary mixtures: (1) tributyl phosphate combined with n-dodecane, a non-polar medium, to represent mixtures which primarily interact via dispersion forces and (2) tributyl phosphate and 1-butanol to represent mixtures with polar functional groups that can also interact via dipole-dipole interactions, including hydrogen bonding. The residuals and the root-mean-square error between the experimental and calculated index values are computed and demonstrate that for miscible liquids in which the average geometry of the cross-interactions can be considered isotropic (e.g., dispersion), the refractive indices of the mixtures can be modeled using composite n and k values derived from volume fractions of the neat liquids. Conversely, in spectral regions where the geometry of the cross-interactions is more restricted and anisotropic (e.g., hydrogen bonding), the calculated n and k values vary from the measured values. The impact of these interactions on the reflectance spectra are then compared by modeling a thin film of the binary mixtures on an aluminum substrate using both the measured and the mathematically computed indices of refraction.

Contact detection algorithm for needle puncturing robot

Contact detection algorithm for needle puncturing robot

New approach of a contact detection algorithm based on a Shortest Link method

Contact detection algorithms based on a Common Plane (CP) are among the most used and investigated, despite not being the most optimal when generating a CP and thus detecting the existence of contact between particles. The generation of the CP is quite expensive in computational terms, for which some algorithms seek to check a possibility of contact between them quickly; and then verify it. For these cases, there are algorithms such as the Shortest Link Method (SLM) that efficiently generate a CP and quickly verify the existence of contact between particles. However, this algorithm has some shortcomings. The main reason for this research is to create a new algorithm based on SLM that can work without its disadvantages.

Multi-Frame Constrained Block Sparse Bayesian Learning for Flexible Tactile Sensing Using Electrical Impedance Tomography

In this paper, we presented a multi-frame constrained block sparse Bayesian learning (MFC-BSBL) reconstruction algorithm to tackle the challenge of poor-quality reconstruction images in electrical impedance tomography (EIT) for tactile sensing. The fundamental idea of MFC-BSBL is to explore the sparsity, intra-frame correlation, and inter-frame correlation of impedance distributions by extending the Bayesian inference framework. To verify the proposed algorithm, we conducted numerical simulations for different cases to identify one, multiple, round, and square targets. The simulation results demonstrated that this method can effectively detect the target positions and shapes by reducing artifacts and noise in the reconstructed images. To demonstrate the application of this approach to real EIT-based tactile sensing, we conducted real-contact detection experiments using the EIT tactile sensor system. Compared with traditional methods, the tactile sensor system using the MFC-BSBL algorithm can achieve accurate contact detection and significantly reduce artifacts and noise.

A 3D Printed Soft Robotic Hand With Embedded Soft Sensors for Direct Transition Between Hand Gestures and Improved Grasping Quality and Diversity.

In this study, a three-dimensional (3D) printed soft robotic hand with embedded soft sensors, intended for prosthetic applications is designed and developed to efficiently operate with new-generation myoelectric control systems, e.g., pattern recognition control and simultaneous proportional control. The mechanical structure of the whole hand ('ACES-V2') is fabricated as a monolithic structure using a low-cost and open-source 3D printer. It minimizes the post-processing required for the addition of the embedded sensors in the hand. These are significant benefits for the robotic hand that features low cost, low weight (313 grams), and anthropomorphic appearance. With the soft position sensors added to the fingers, the fingers' positions can be monitored to avoid self-collision of the hand. Besides, it allows a robotic prosthetic hand to eliminate the conventional way of returning to the neutral full open position when switching from one type of gesture to another. This makes the transition between the hand gestures much faster, more efficient, and more intuitive as well. Further, initial contact detection of each finger is achieved for the preshaping of multi-finger grasps, e.g., tripod grip and power grasps, to improve the stability and quality of the grasps. Combinations of different gestures allow the hand to perform multi-stage grasps to seize and carry multiple objects simultaneously. It can potentially augment the hand's dexterity and grasping diversity. Providing direct transition between the hand gestures and improved grasping quality and diversity are the primary contributions of this study.

Fingertip Contact Detection for a Multi-fingered Under-actuated Robotic Hand using Density-based Clustering Method

Fingertip Contact Detection for a Multi-fingered Under-actuated Robotic Hand using Density-based Clustering Method

Quantifying the errors in animal contacts recorded by proximity loggers

AbstractAutomated contact detection by means of proximity loggers permits the measurement of encounters between individuals (animal‐animal contacts) and the time spent by individuals in the proximity of a focal resource of interest (animal‐fixed logger contacts). The ecological inference derived from contact detection is intrinsically associated with the distance at which the contact occurred. But no proximity loggers currently exist that record this distance and therefore all distance estimations are associated with error. Here we applied a probabilistic approach to model the relationship between contact detection and inter‐logger distance, and quantify the associated error, on free‐ranging animals in semi‐controlled settings. The probability of recording a contact declined with the distance between loggers, and this decline was steeper for weaker radio transmission powers. Even when proximity loggers were adjacent, contact detection was not guaranteed, irrespective of the radio transmission power. Accordingly, the precision and sensitivity of the system varied as a function of inter‐logger distance, radio transmission power, and experimental setting (e.g., depending on animal body mass and fine‐scale movements). By accounting for these relationships, we were able to estimate the probability that a detected contact occurred at a certain distance, and the probability that contacts were missed (i.e., false negatives). These calibration exercises have the potential to improve the predictability of the study and enhance the applicability of proximity loggers to key wildlife management issues such as disease transmission rates or wildlife use of landscape features and resources.

A discrete element method with spherical harmonics for irregular granular materials based on the level set contact algorithm

<p indent=0mm>To calculate the mechanical properties of irregular granular materials in natural or industrial fields, a discrete element model based on spherical harmonics that can describe arbitrarily shaped particles is developed. Considering the uneven surfaces and multiple contact points of the spherical harmonic elements, a contact model of arbitrary shapes based on the level set algorithm is developed to calculate the contact direction and overlap between the elements. In this model, spherical harmonic elements with different shapes are discretized into a zero level set function and a discrete spatial-level set function composed of a series of points. In addition, the contact detection between elements is transformed into a solution of two level set functions. All zero level set points are brought into the spatial-level set function of the neighboring element, and the multiple contact points and forces between the two neighboring elements are determined via trilinear interpolation. The elastic collision of a single particle with a wall, the free fall of a particle, and the packing process of multiple particles are simulated using the discrete element method, and the evolution of the translational and rotational kinetic energy of particles over time is studied to validate the discrete element model of the spherical harmonic function based on the level set method. The results show that the discrete element model of spherical harmonic functions based on the level set method can be used to calculate the contact forces between elements. Meanwhile, the energy of the granular system remains constant during the elastic collision, and the system energy decays during the inelastic collision until the kinetic energy approaches zero. Based on the aforementioned method, the influence of uneven surfaces on the packing fraction and average coordination number of granular materials is analyzed, and an effective discrete element model is provided for the numerical simulation of irregular granular materials.

Combined finite-discrete element method for modeling the interaction between single PDC cutter and brittle rock

This paper describes a combined finite-discrete element method for simulating the interaction between single PDC cutter and brittle rock. The proposed method is capable of capturing the nucleation, propagation, branching, and coalescence of cracks as well as the contact between fragments during the cutting process. A detailed description of the method is provided. A linear Mohr-Coulomb criterion with tension cutoff is applied to identify which edge is failure based on the normal and shear stresses estimated from the triangular elements abutting from the edge. The Munjiza-NBS algorithm and Simple-Common-Plane (SCP) contact algorithm are used for the contact detection and interaction, respectively. The method is then validated against the theoretical results of Brazilian disc test and uniaxial compressive strength test. The results demonstrate that the proposed method is of high accuracy, especially before rock failure, because the cracks in the model are introduced on the fly by splitting the nodes where and when needed. Finally, several typical cases of the interaction between single PDC cutter and brittle rock are performed. The numerical results indicate that the wedging effect is significant, leading to the formation of large size chippings for brittle rock cutting.

Risco: a COVID-19 mobile application with contact tracing

The pandemic from 2019 has led us to the implementation of different protocols to reduce the number of infections per day and avoid the overwhelming of the health centers. Until 2021, the implemented methodologies to stop the continuous growth of the pandemic have greatly reduced the infections, but they are not enough for the society. Thus, we propose Risco, an application that will aid not only in the reduction of infections via the early detection of contact with infected people by providing real time analytics and contact tracing support but improve the awareness of the user location data.

Foot angular kinematics measured with inertial measurement units: A reliable criterion for real-time gait event detection

Accurate and reliable real-time detection of gait events using inertial measurement units (IMUs) is crucial for (1) developing clinically meaningful gait parameters to differentiate normal and impaired gait or (2) creating patient-tailored gait rehabilitation strategies or control of prosthetic devices using feedback from gait phases. However, most previous studies focused only on algorithms with high temporal accuracy and neglected the importance of (1) high reliability, i.e., detecting only and all true gait events, and (2) real-time implementation. Thus, in this study, we presented a novel approach for initial contact (IC) and terminal contact (TC) detection in real-time based on the measurement of the foot orientation. Unlike foot/shank angular velocity and acceleration, foot orientation provides physiologically meaningful kinematic features corresponding to our observational recognition of IC and TC, regardless of the walking modality. We conducted an experimental study to validate our algorithm, including seven participants performing four walking/running activities. By analyzing 5,555 ICs/TCs recorded during the tests, only our algorithm achieved a sensitivity and precision of 100%. Our obtained temporal accuracy (mean ± standard deviation of errors ranging from 0 ± 3 to 6 ± 5 time samples; sampling frequency: 100 Hz) was better than or comparable to those reported in the literature. Our algorithm’s performance does not depend on thresholds and gait speed/modality, and it can be used for feedback-based therapeutic gait training or real-time control of assistive or prosthetic technologies. Nevertheless, its performance for pathological gait must be validated in the future. Finally, we shared the codes and sample data on https://www.ncbl.ualberta.ca/codes.

Design of a Millimeter-Wave Radar Remote Monitoring System for the Elderly Living Alone Using WIFI Communication.

In response to the current demand for the remote monitoring of older people living alone, a non-contact human vital signs monitoring system based on millimeter wave radar has gradually become the object of research. This paper mainly carried out research regarding the detection method to obtain human breathing and heartbeat signals using a frequency modulated continuous wave system. We completed a portable millimeter-wave radar module for wireless communication. The radar module was a small size and had a WIFI communication interface, so we only needed to provide a power cord for the radar module. The breathing and heartbeat signals were detected and separated by FIR digital filter and the wavelet transform method. By building a cloud computing framework, we realized remote and senseless monitoring of the vital signs for older people living alone. Experiments were also carried out to compare the performance difference between the system and the common contact detection system. The experimental results showed that the life parameter detection system based on the millimeter wave sensor has strong real-time performance and accuracy.

A semi-online spatial wheel-rail contact detection method

ABSTRACT Online spatial wheel-rail contact detection with elastic contact hypothesis has a heavy computational burden. The traditional end-to-end look-up table method can significantly improve search efficiency. However, It has high storage requirements. In this paper, a semi-online approach is proposed to alleviate the contradiction between the online and the offline method. First, a new algorithm of normal maximum penetration for unworn rail profiles is proposed. The algorithm is only required to calculate the closest proximity of the rail feature point to the wheel contact trace contact curve. Then, derived curves with different yaw angles are pre-stored in a new look-up table for online dynamics simulation usage. The proposed look-up table reduces the required generation time and the storage space. The numerical simulation results show that the proposed method can be used for train dynamics simulation under earthquakes. Besides, the search speed is much faster than that of the online method.

Development of an integrated biomechanics informatics system with knowledge discovery and decision support tools for research of injury prevention and performance enhancement

The field of biomechanics involves integrating a variety of data types such as waveform, video, discrete, and performance. These different sources of data must be efficiently and accurately associated to provide meaningful feedback to athletes, coaches, and healthcare professionals to prevent injury and improve rehabilitation/performance. There are many challenges in biomechanics research such as data storage, standardization, review, sharing, and accessibility. Data is stored in different formats, structures, and locations such as physical hard drives or Dropbox/Google Drive, leading to issues during sharing and collaboration. Data is reviewed and analyzed through different software applications that need to be downloaded and installed locally before they are available for use. An integrated biomechanics informatics system (IBIS) built based on the core principles in medical imaging informatics provides a solution to many of these challenges. The system provides a secure web-based platform that will be accessible remotely for authenticated users to upload, share, and download data. The web-based application includes built-in data viewers that are streamlined for reviewing multimedia data and decision support/knowledge discovery tools. These tools include automatic foot contact detection for pre-processing, built-in statistical analysis applications for longitudinal and cross-study analysis, and a multi-institutional collaboration module. The IBIS system creates a centralized hub to support multi-institutional collaborative biomechanics research and analysis that is remotely accessible to all users including athletes, coaches, researchers, and clinicians generating a novel streamlined research workflow, data analysis, and knowledge discovery process.

Automated Calculation of Cochlear Implant Electrode Insertion Parameters in Clinical Cone-Beam CT.

Automated processing of postoperative clinical cone-beam CT (CBCT) of cochlear implant (CI) patients can be used to accurately determine electrode contacts and integrated with an atlas-based mapping of cochlear microstructures to calculate modiolar distance, angular insertion distance, and scalar location of electrode contacts. Hearing outcomes after CI surgery are dependent on electrode placement. CBCT is increasingly used for in-office temporal bone imaging and might be routinely used for pre- and post-surgical evaluation. Thirty-six matched pairs of pre- and postimplant CBCT scans were obtained. These were registered with an atlas to model cochlear microstructures in each dataset. Electrode contact center points were automatically determined using thresholding and electrode insertion parameters were calculated. Automated localization and calculation were compared with manual segmentation of contact center points as well as manufacturer specifications. Automated electrode contact detection aligned with manufacturer specifications of spacing and our algorithms worked for both distantly- and closely spaced arrays. The average difference between the manual and the automated selection was 0.15 mm, corresponding to a 1.875 voxel difference in each plane at the scan resolution. For each case, we determined modiolar distance, angular insertion depth, and scalar location. These calculations also resulted in similar insertion values using manual and automated contact points as well as aligning with electrode properties. Automated processing of implanted high-resolution CBCT images can provide the clinician with key information on electrode placement. This is one step toward routine use of clinical CBCT after CI surgery to inform and guide postoperative treatment.

An extension of the Fourier series-based particle model to the GJK-based contact detection and resolution framework for DEM

An extension of the Fourier series-based particle model to the GJK-based contact detection and resolution framework for DEM