Contact Detection Research Articles

Fast contact detection for ellipsoids using optimization approaches

AbstractThe paper is concerned with fast and robust contact detection methods for arbitrary ellipsoids. An iterative procedure, namely the Levenberg‐Marquardt method, based on the common normal concept for parametric ellipsoids, is employed together with an implementation of the widely used GJK algorithm for comparison. The performance and accuracy of both are analysed and compared to each other on the basis of two test sets, each containing a total of 70 000 pairs of prolates or oblates. Emphasis is placed on the specific error measure relating the iterative solution to the exact one, which was chosen to be the maximum angle between the normal vector and the distance vector between two ellipsoids. The results indicate increased performance when using the Levenberg‐Marquardt method over the GJK algorithm with no loss of accuracy.

Rocking sensitivity of a dual‐block stack ‐ Numerical simulation and experimental evidence

AbstractHistoric monuments, drywall structures, and graphite blocks in AGR nuclear power plants are block‐like structures that have to withstand rocking when subject to seismic excitation of their base, which can lead to overturning of some of their components and results in the collapse of the whole structure. We revisit the known nonlinear equations of motion for a dual‐block stack and present the conditions for transition between the eight possible rocking configurations (due to initiation of rocking, opening of new contacts, and collisions between blocks). An algorithm for the numerical simulation of rocking of the dual‐block stack is developed using the Newmark integration method, the Newton‐Raphson iteration method, and a novel contact detection and resolution procedure. The algorithm is used to evaluate rocking stability of five dual‐block stacks, one of which is compared to the results available in the literature. In parallel, a novel experimental program is designed and implemented, to validate the numerically obtained results using a shaking table. While most of the excitation conditions leading to stable rocking and limit values leading to overturning have been successfully validated, some discrepancies between the numerically and experimentally obtained results still exist and point to the need for improvement of the algorithm used, possibly through a more realistic energy‐loss mechanism. Most importantly, we have confirmed the known theoretical prediction that splitting a single block into two half‐size blocks benefits its rocking stability.

Eulerian framework for contact between solids represented as phase fields

Mechanical contact between solids is almost exclusively modeled in Lagrangian frameworks. While these frameworks have been developed extensively and applied successfully to numerous contact problems, they generally require complex algorithms for contact detection and resolution. These challenges become particularly important when contact appears between solids with evolving boundaries, such as in systems where crystals grow in a constrained space. In this work, we introduce a fully Eulerian finite element framework for modeling contact between elastic solids tailored towards problems including evolving and intricate surfaces. The proposed approach uses a phase-field method that involves a diffuse representation of geometries on a fixed mesh, simplifying the modeling of evolving surfaces. Our methodology introduces a novel volumetric contact constraint based on penalty body forces, efficiently resolving the interpenetration of solids. We showcase the validity and versatility of our method through numerical examples, highlighting its ability to accurately capture complex solid–solid interactions. The Eulerian phase-field formulation greatly simplifies contact detection and its resolution. Furthermore, the framework can be straightforwardly coupled with other physical phenomena through the inclusion of multiple energy terms in the evolution of the phase-field. This enables multiphysics modeling, potentially providing a valuable tool for a wide range of applications involving chemically or physically evolving deformable solids in contact, as they commonly occur in deterioration processes of porous media.

Non-spherical Particle Modelling Approach in Discrete Element Method and its Validations

The discrete element method (DEM) is widely used for investigating the mechanical behaviours of complex physical system consisting of particles. In nature, the physical system such as rock and soil system, sand or flour are all composed of particles with different shapes. The particle shape can considerably influence nature characteristics in DEM simulation. Developing an effective particle shapes representation approach is a valuable task to improve the DEM modelling techniques. In this study, a super-quadrics function is introduced to represent the non-spherical particle shape. Furthermore, the corresponding contact detection and calculation algorithm named “deepest point method” is also explained to describe the complex contact relationships and calculate the contact forces between two irregular particles. At last, sandpile collapse simulations were conducted to validate the accuracy of the proposed approach. The numerical results indicate that the non-spherical particle modelling approach in this study can easily simulate most nature shape of particle system.

Vision and Tactile Robotic System to Grasp Litter in Outdoor Environments

The accumulation of litter is increasing in many places and is consequently becoming a problem that must be dealt with. In this paper, we present a manipulator robotic system to collect litter in outdoor environments. This system has three functionalities. Firstly, it uses colour images to detect and recognise litter comprising different materials. Secondly, depth data are combined with pixels of waste objects to compute a 3D location and segment three-dimensional point clouds of the litter items in the scene. The grasp in 3 Degrees of Freedom (DoFs) is then estimated for a robot arm with a gripper for the segmented cloud of each instance of waste. Finally, two tactile-based algorithms are implemented and then employed in order to provide the gripper with a sense of touch. This work uses two low-cost visual-based tactile sensors at the fingertips. One of them addresses the detection of contact (which is obtained from tactile images) between the gripper and solid waste, while another has been designed to detect slippage in order to prevent the objects grasped from falling. Our proposal was successfully tested by carrying out extensive experimentation with different objects varying in size, texture, geometry and materials in different outdoor environments (a tiled pavement, a surface of stone/soil, and grass). Our system achieved an average score of 94% for the detection and Collection Success Rate (CSR) as regards its overall performance, and of 80% for the collection of items of litter at the first attempt.

Neuron Contact Detection Based on Pipette Precise Positioning for Robotic Brain-Slice Patch Clamps.

A patch clamp is the "gold standard" method for studying ion-channel biophysics and pharmacology. Due to the complexity of the operation and the heavy reliance on experimenter experience, more and more researchers are focusing on patch-clamp automation. The existing automated patch-clamp system focuses on the process of completing the experiment; the detection method in each step is relatively simple, and the robustness of the complex brain film environment is lacking, which will increase the detection error in the microscopic environment, affecting the success rate of the automated patch clamp. To address these problems, we propose a method that is suitable for the contact between pipette tips and neuronal cells in automated patch-clamp systems. It mainly includes two key steps: precise positioning of pipettes and contact judgment. First, to obtain the precise coordinates of the tip of the pipette, we use the Mixture of Gaussian (MOG) algorithm for motion detection to focus on the tip area under the microscope. We use the object detection model to eliminate the encirclement frame of the pipette tip to reduce the influence of different shaped tips, and then use the sweeping line algorithm to accurately locate the pipette tip. We also use the object detection model to obtain a three-dimensional bounding frame of neuronal cells. When the microscope focuses on the maximum plane of the cell, which is the height in the middle of the enclosing frame, we detect the focus of the tip of the pipette to determine whether the contact between the tip and the cell is successful, because the cell and the pipette will be at the same height at this time. We propose a multitasking network CU-net that can judge the focus of pipette tips in complex contexts. Finally, we design an automated contact sensing process in combination with resistance constraints and apply it to our automated patch-clamp system. The experimental results show that our method can increase the success rate of pipette contact with cells in patch-clamp experiments.

A CPU parallelized coupling framework for constrained flexible multibody system and granular matter based on contact-graph

This paper proposes a coupling model for simulating the interaction between particles and the flexible multibody system. The flexible rods are described using the Absolute Nodal Coordinate Formulation, and various types of contacts, including particle-particle, particle-rod, particle-rigid body contacts, and contacts within multibody objects, are considered. The contact detection is improved by combining space partitioning techniques and the bounding box method. A data structure based on a contact graph is introduced to store the contact relationships efficiently. The discrete element system and multibody system are coupled through serial time integration, with data exchanges at the program level. Numerical examples demonstrate the validity of the proposed model. Moreover, the model is applied to simulate the asteroid soil sampling with flexible brush sampler, showing good agreement with experimental data. The analysis of engineering examples provides insights for sampler design, and show the model's engineering value.

A multifunctional helical fiber operated in non-contact/contact dual-mode sensing aiming for HMI/VR applications

The demand for information exchange between humans and machines or virtual spaces is growing rapidly. However, traditional contact sensing makes the spread of bacteria and viruses, and single sensing also limits the development. Hence, as an innovative product, a non-contact/contact dual-mode sensor has to come into being, which consists of stretchable bacterial cellulose (BC)-BC/graphene (Gr) helical fibers. The helical fiber with a sheath-core structure, and the degradable BC as the sheath and BC/Gr as the core, which exhibit a tensile strength of 113 MPa and elongation at a break of 477%. Under non-contact mode, the capacitance change (ΔC/C0) arrives to –0.6 (–60%) when the approaching distance is 0.5 cm, and the remote communication through capacitance changes when it is sewn on the lab-gown as a wearable wireless non-contact phone. Under contact mode, action guidance and detection are achieved successfully through interaction with virtual space. All in all, this work will lead to a new era of non-contact human-machine interfaces (HMI) and dual-mode sensors, providing a solid research foundation and leading thinking for wearable electronic products that require non-contact or multi-function Internet of Things (IoT) and virtual reality (VR) field.

Contact detection with multi-information fusion for quadruped robot locomotion under unstructured terrain

Contact detection with multi-information fusion for quadruped robot locomotion under unstructured terrain

Lock-in photothermal method for in-plane thermal diffusivity measurements using arrayed temperature sensors on suspended SiNx membranes.

A device consisting of a line- or spiral-shaped temperature sensor array on a two-dimensional (2D) silicon nitride (SiNx) membrane of thickness 50 or 150nm is developed for use in the lock-in photothermal method to determine the in-plane thermal diffusivity of SiNx membranes in air and in vacuum. The results of 2D heat diffusion are analyzed by the quadrupole method, and the system is approximated to the one-dimensional (1D) fin standing in a surrounding media (the fin approximation). The results show that 2D thermal diffusion on the membrane is affected not only by heat exchange with the surrounding environment but also by parallel thermal diffusion caused by heat conduction in the air along the membrane surface. The measurement using photothermal heating and contact detection of the temperature response enables the phenomenon to be detected consistently at a wide frequency range of temperature waves (50-1000Hz). The measured thermal diffusivity values of the SiNx membrane are much smaller than those of bulk material, which can be reasonably considered an effect of the confined state of the phonon in the nanoscale geometry of the membrane.

Sharing imagery and analysis tools in a simulated submarine control room

We examined the impact of sharing periscope imagery and analysis tools in eighteen five-member teams (Sonar, Periscope, 2xTrack Motion Analysts, Track Manager) who undertook simulated submarine patrol tasks. Compared to a baseline condition, sharing imagery to team members increased perceived individual workload, with no improvement to team performance (tactical picture accuracy). When both imagery and analysis tools were shared, perceived workload increased and tactical picture compilation was more accurate. Despite this improved tactical picture for the imagery and analysis tools condition, there was no advantage to mission completion (rendezvous/close contact detection) or situation awareness. In contrast to the increased subjective workload, individuals in teams provided with shared imagery (with or without tools) had a lower physiological response (heart rate, electrodermal) to task demands compared to the baseline condition. Sharing imagery and analysis tools likely benefited tactical picture compilation by enabling dynamic task redistribution and multiple streams of concurrent data analysis.

Fatigue Driving Detection Method Based on IPPG Technology

Physiological signal index can accurately reflect the degree of fatigue, but the contact detection method will greatly affect the driver's driving. This paper presents a non-contact method for detecting tired driving. It uses cameras and other devices to collect information about the driver's face. By recording facial changes over a period and processing the captured video, pulse waves are extracted. Then the frequency domain index and nonlinear index of heart rate variability were extracted by pulse wave characteristics. Finally, the experiment proves that the method can clearly judge whether the driver is tired. In this study, the Imaging Photoplethysmography (IPPG) technology was used to realise non-contact driver fatigue detection. Compared with the non-contact detection method through identifying drivers' blinking and yawning, the physiological signal adopted in this paper is more convincing. Compared with other methods that detect physiological signals to judge driver fatigue, the method in this paper has the advantages of being non-contact, fast, convenient and available for the cockpit environment.

Revolutionizing granular matter simulations by high-performance ray tracing discrete element method for arbitrarily-shaped particles

It remains a challenge for discrete element method to simulate large-scale systems with arbitrarily shaped particles. This paper presents a novel approach called Ray Tracing Discrete Element Method (RTDEM) to offer ultra-high efficiency in simulating particles with arbitrary shapes. In RTDEM, we use a triangular mesh to represent the surface of a particle for greater flexibility in shape representation. Template meshes are further introduced to group particles of different shapes to save computing memory. Key to RTDEM are innovative ray tracing-based algorithms specially designed for accurate and efficient contact detection and resolution between arbitrarily shaped particles. Based on the RT algorithms, discrete potential field functions are further proposed for the discrete mesh vertices and facets to define energy-conservative contact models that include vertex-potential, facet-potential models, and their combination. The integration of these key elements into RTDEM offers a whole new DEM framework that readily empowers any parallel computing architecture for high acceleration on granular media modeling. It matches particularly well with the Graphics Processing Units (GPUs) to fully unleash the computing power of ray tracing cores for large-scale DEM simulations of arbitrarily shaped particles, even on a personal computer with a common gaming GPU card.

The Facets of Intangible Heritage in Southern Chinese Martial Arts: Applying a Knowledge-driven Cultural Contact Detection Approach

Investigating the intangible nature of a cultural domain can take multiple forms, addressing, for example, the aesthetic, epistemic, and social dimensions of its phenomenology. The context of Southern Chinese martial arts is of particular significance, as it carries immaterial components of all these aspects: The technical and stylistic framework of a martial art system; the imagery associated to movements; and the transmission of knowledge orally, practically, or through influence, are but examples of intangible characteristics that can and should be captured, not unlike cultural artifacts. The latter case—the one of formalizing cultural influence through its various forms of evidenceis emblematic as well as largely untrodden ground. A previous attempt at detecting cultural influence computationally was made in the context of Roman archaeology, though the binding of that early effort with the domain model was tight; also, there has hardly been any prior dedicated effort to model the martial arts domain through ontologies. In this article, we present the realization of the full cycle of a computational approach to investigating cultural contact in Southern Chinese martial arts. The entire approach is predicated upon the usage of standards and techniques of the Semantic Web and formal knowledge. Starting from a modular domain ontology, which models martial arts independently of the goal of capturing cultural influence, we perform knowledge extraction from archival material from the Hong Kong Martial Arts Living Archive and generate a dataset of the results modeled after said ontology. Then, we combine the resulting knowledge base with a rule model that represents ways to infer knowledge of potential contact between cultures based on the evidence present in the knowledge base. The results offer an insight into how an inference-based computational model can be applied to detect interesting facts even in the as-yet underexplored domain of intangible cultural heritage. The implemented workflow shows that the full-cycle employment of semantic technologies can offer the ground truth required for largely different approaches, such as statistical and machine learning ones, to operate.

Evaluating the performance of wearable devices for contact tracing in care home environments

COVID-19 has had a devastating impact worldwide, including in care homes where there have been substantial numbers of cases among a very vulnerable population. A key mechanism for managing exposure to the virus and targeting interventions is contact tracing. Unfortunately, environments such as care homes that were most catastrophically impacted by COVID-19 are also those least amenable to traditional contact tracing. A promising alternative to recall and smartphone-based contact tracing approaches is the use of discrete wearable devices that exploit Bluetooth Low Energy (BLE) and Long-Range Wide Area Network (LoRaWAN) technologies. However, the real-world performance of these devices in the context of contact tracing is uncertain. A series of experiments were conducted to evaluate the performance of a wearables system that is based on BLE and LoRaWAN technologies. In each experiment, the number of successful contacts was recorded and the physical distance between two contacts was compared to a calculated distance using the Received Signal Strength Indication (RSSI) to determine the precision, error rate, and duration of proximity. The overall average system contact detection success rate was measured as 75.5%; when wearables were used as per the manufacturer’s guidelines the contact detection success rate increased to 81.5%, but when obstructed by everyday objects such as clothing or inside a bag the contact detection success rate was only 64.2%. The calculated distance using RSSI was close to the physical distance in the absence of obstacles. However, in the presence of typical obstacles found in care home settings, the reliability of detection decreased, and the calculated distance usually appeared far from the actual contact point. The results suggest that under real-world conditions there may be a large proportion of contacts that are underestimated or undetected.

A DEM-based model for predicting worn surface morphology of ductile metal target by single-particle erosion via energy conversion and geometric reconstruction

The DEM (Discrete Element Method) can simulate target wear due to erosion by impacts of a number of particles. Predicting worn morphology of target by single-particle erosion is the basis of that by multiple-particle erosion. However, the current DEM prediction models for single-particle erosion are aimed at total volume loss rather than worn morphology of target. A DEM-based model for predicting crater-shaped morphology of target by single-particle erosion has been developed depending on energy conversion and geometric reconstruction. In our model, target is represented by a shell element in contact detection, while is taken as a statistically isotropic rough surface covered with deformable asperities in contact force calculation. Then, a modified contact stiffness formula is presented for addressing the elastic-plastic contact characteristic of the two contact objects during erosion. In prediction, volume losses of target due to deformation damage and cutting removal are separately measured based on normal and tangential collision energies using DEM, and the crater-shaped morphology is predicted via geometric reconstruction. Through numerical tests, our model has been verified to be an effective model for predicting the crater-shaped morphology of target by single-particle erosion in response to different impingement angles and at least two different target materials.

Comparison of contact treatment methods for rigid polyhedral discrete element models

Blocky rock and stone structures (such as jointed rocks mass, masonry structures and railway ballast) are often submitted to dynamic effects. Their mechanical behaviour can be simulated with the discrete element method (DEM) using polyhedral elements. DEM models differ in how they compute the contact forces. Several studies have compared different contact constitutive laws, but little information is available in the literature on which contact treatment method (i.e. number of contacts between two elements, contact detection, contact orientation, area and overlap computation) to choose. The inclined slope, the perpendicular impact and the rocking block problems were simulated and applied as benchmark tests in the present study to compare three most popular polyhedral DEM contact treatment models for rigid elements, namely the Eliáš (available in Yade), the Gilbert-Johnson-Keerthi (GJK, widely implemented, here tested with PFC3D) and the Sub-Contact model (available in 3DEC), to see which ones could be precisely calibrated to analytic and experimental solutions. Sensitivity studies were also carried out on the effect of subdivision density of element surfaces and on the admissible timestep length. Experiences showed that while there are serious doubts about the applicability of the Eliáš volumetric model as it is sensitive to both variations in geometry and the results vary randomly with the timestep length, the GJK model is suitable to simulate granular materials because of its computational efficiency and robustness, and the Sub-Contact method is the proper choice to model structures where the contact surfaces are relatively large, as it operates multiple contacts between two elements and gives information about the force distribution on the surface of the elements.

Ultrasonic Aspirator for Tissue Contact Detection: An Online Classification on Time-Series.

The goal of neurosurgical tumor surgery is to remove the tumor completely without damaging healthy brain structures and thereby impairing the patient's neurological functions. This requires careful planning and execution of the operation by experienced neurosurgeons using the latest intraoperative technologies to achieve safe and rapid tumor reduction without harming the patient. To achieve this goal, a standard ultrasonic aspirator designed for tissue removal is equipped with additional intraoperative tissue detection using machine learning methods.Since decision-making in a clinical context must be fast, online contact detection is critical. Data are generated on three types of artificial tissue models in a CNC machine-controlled environment with four different ultrasonic aspirator settings. Contact classification on artificial tissue models is evaluated on four classification algorithms: change point detection (CPD), random forest (RF), recurrent neural network (RNN) and temporal convolutional network (TCN). Data preprocessing steps are applied, and their impacts are investigated. All methods are evaluated on five-fold cross-validation and provide generally good results with a performance of up to 0.977±0.007 in mean F1-score. Preprocessing the data has a positive effect on the classification processes for all methods and consistently improves the metrics. Thus, this work indicates in a first step that contact classification is feasible in an online context for an ultrasonic aspirator. Further research is necessary on different tissue types, as well as hand-held use to more closely resemble the intraoperative clinical conditions.

Continuous frequent contact detection over moving objects

Continuous frequent contact detection over moving objects

A computational workflow to study CO2 transport in porous media with irregular grains: Coupling a Fourier series-based approach and CFD

Understanding CO2 transport in porous media is important for enhanced oil recovery and CO2 sequestration. In this study, we aimed to develop a computational workflow to automatically simulate CO2 transport in porous media, including generating digital porous media from a grain morphological perspective, a pipeline, and pore-scale modeling. A method for generating porous media using a Fourier series-based approach was proposed for this workflow. Contact detection introduced the Floyd-Warshall algorithm to improve the computational efficiency and application scope of the method. Furthermore, the simultaneous application of parametric equations and grid mapping makes the output results diverse. A pipeline was built to link the proposed method with pore-scale modeling to automate the workflow. Drawing on the developed computational workflow, we simulated CO2 transport in porous media and discussed the effects of varying the different pore structures, capillary numbers and wettabilities. In different pore structures, the dual-porosity model is easily broken through by CO2 causing a small swept area making its oil recovery lower than the single-porosity model. In the capillary number, the CO2-free oil recovery period decreased with an increasing capillary number in the media. The concomitant imbibition in the low capillary number increased swept area and oil recovery but can lead to economic and time losses. At the wettabilities, the maximum recovery was achieved with weak CO2 wetting. This computational workflow can be used as an effective tool to investigate CO2 transport within porous media, contributing to the design and application of innovative enhanced CO2 sequestration and oil recovery method.