bluuebunny/crossref_metadata_2025_split huggingface dataset:
Dynamic 3D Mesh Reconstruction Based on Nonrigid Iterative Closest-Farthest Points Registration
Authors: Tajdari Farzam , Kwa Felix , Versteegh Christiaan , Huysmans Toon , Song Yu 
Published: November 2022

Abstract
Fitting apparel and apparel in performing different activities is essential for the functional yet comfortable experience of the user. 4D scans, i.e. 3D scans in continuous timestamps, of the body (part) in performing those activities are the basis for the design of garments/apparel in 4D. In this paper, we proposed a semi-automatic workflow for constructing 4D scans of the body parts with the emphasis on registering noisy scans at a given timestamp. Continuous 3D scans regarding the moving body parts are captured first from different depth cameras from different view angles. In a given timestamp, the collected 3D scans are roughly aligned to a template using the rigid Iterative Closest Points (ICP) algorithm. Then these scans are further registered using a newly proposed non-rigid Iterative Closest-Farthest Points (ICFP) algorithm, in which correspondences between the source and the target are established by either closest or farthest points based on the newly defined logical distance concept and the probability theory. Experimental results indicated that the ICFP method is robust against noise and the scanning accuracy can be as high as 3.4 %. It also reveals that, for the human foot, the differences of ball width and ball angles between the loaded and the unloaded situation can be as large as 8 mm and 2 degrees, respectively. This highlights the importance of using 4D scan in designing garments and apparel.
Automated Weld Path Generation Using Random Sample Consensus and Iterative Closest Point Workpiece Localization
Authors: Hill Tristan , Canfield Stephen , Shelton Robert 
Published: November 2022

Abstract
Jobs performed by small to medium enterprises (SMEs) are infrequently automated due to high setup costs and lack of technical expertise needed for robot training, however productivity and worker safety can be improved in SMEs with the use automated tooling. In a traditional automated manufacturing environment, tasks such a welding or painting are accomplished through execution of pre-programmed tool motions which rely on the location and orientation of the workpiece to be fixed and known. The lack of this spatial information is typically treated through positioning of the workpiece with respect to the robot arm using jigs or fixtures which are costly in initial setup and not easily modified. Further, the resulting toolpath associated with a desired task is typically defined through manual teaching resulting in a path appropriate for an individual job. For this reason, SMEs requiring variation in part geometry or arrangement are not commonly automated. This work presents a method for automated weld path generation for a 6DOF co-bot arm using random sample consensus (RANSAC) and iterative closest point (ICP) workpiece localization from LiDAR point clouds. Scans from a low cost 2D LiDAR mounted to the co-bot arm are used to generate 3D point clouds of the workspace scene with the Robot Operating System (ROS). The Point Cloud Library (PCL) is used to compare the generated point cloud with a CAD model to produce a rigid transformation to localize the workpiece. The estimated pose of the workpiece with respect to a fixed frame is used offline to generate a weld path as series of tool poses. An example welding processes in which two square tubes are joined through weldment are investigated and a physical implementation of the method is demonstrated using a 2D LiDAR mounted to a 6DOF co-bot arm.
A Multi-Fidelity Approach for Reliability Assessment Based on the Probability of Model Inconsistency
Authors: Pidaparthi Bharath , Missoum Samy 
Published: November 2022

Abstract
Most multi-fidelity schemes rely on regression surrogates, such as Gaussian Processes, to combine low- and high-fidelity data. Contrary to these approaches, we propose a classification-based multi-fidelity scheme for reliability assessment. This multi-fidelity technique leverages low- and high-fidelity model evaluations to locally construct the failure boundaries using support vector machine (SVM) classifiers. These SVMs can subsequently be used to estimate the probability of failure using Monte Carlo Simulations. At the core of this multi-fidelity scheme is an adaptive sampling routine driven by the probability of misclassification. This sampling routine explores sparsely sampled regions of inconsistency between low- and high-fidelity models to iteratively refine the SVM approximation of the failure boundaries. A lookahead check, which looks one step into the future without any model evaluations, is employed to selectively filter the adaptive samples. A novel model selection framework, which adaptively defines a neighborhood of no confidence around low fidelity model, is used in this study to determine if the adaptive samples should be evaluated with high- or low-fidelity model. The proposed multi-fidelity scheme is tested on a few analytical examples of dimensions ranging from 2 to 10, and finally applied to assess the reliability of a miniature shell and tube heat exchanger.
Multi-Axes Series Elastic Actuation: A Computer Model
Authors: Zhang Haohan 
Published: November 2022

Abstract
This paper proposes a novel approach to providing series elastic actuation for parallel robots. Current series elastic actuators (SEA) are limited to providing single degree-of-freedom (DoF) series elastic actuation. To provide series elastic actuation for each DoF of a parallel robot, an SEA unit must be added to each active joint. In this paper, we introduce a new approach: we recognize a parallel robot as a multi-axes actuator, and we connect the robot platform and the load through a parallel elastic element which has an approximately linear and decoupled wrench-displacement relationship in each dimension. We first introduce the structure of this elastic element and demonstrate its linearity and decoupling properties through a computer model. A constant diagonal stiffness matrix is obtained to relate the six-dimensional wrench and deflection of the elastic element. Then, an integration between this elastic element and a Stewart Platform is achieved in simulation. An experiment is then performed to control the robot platform to follow an input motion of the load while applying zero wrench on the load, which is inspired by a common task performed by rehabilitation robots. Using this approach, we show that the force control of the robot can be transformed into position control while providing necessary compliance between the robot and its load.
Conceptual Design of Cellular Auxetic Systems With Passive Adaptation to Loading
Authors: Prendergast Joshua , Oddiraju Manaswin , Nouh Mostafa , Chowdhury Souma 
Published: November 2022

Abstract
Auxetics refer to a class of engineered structures which exhibit an overall negative Poisson’s ratio. These structures open up various potential opportunities in impact resistance, high energy absorption, and flexible robotics, among others. Interestingly, auxetic structures could also be tailored to provide passive adaptation to changes in environmental stimuli — an adaptation of this concept is explored in this paper in the context of designing a novel load-adaptive gripper system. Defining the design in terms of repeating parametric unit cells from which the finite structure can be synthesized presents an attractive computationally-efficient approach to designing auxetic structures. This approach also decouples the optimization cost and the size of the overall structure, and avoids the pitfalls of system-scale design e.g., via topology optimization. In this paper, a surrogate-based design optimization framework is presented to implement the concept of passively load-adaptive structures (of given outer shape) synthesized from auxetic unit cells. Open-source meshing, FEA and Bayesian Optimization tools are integrated to develop this computational framework, enhancing it adopt-ability and extensibility. Demonstration of the concept and the underlying framework is performed by designing a simplified robotic gripper, with the objective to maximize the ratio of towards-load (gripping) horizontal displacement to the load-affected vertical displacement. Optimal auxetic cell-based design generated thereof is found to be four times better in terms of exhibited contact reaction force when compared to a design obtained with topology optimization that is subjected to the same specified maximum loading.
On Spiral Folding of Planar Membranes With Finite Thickness and Curved Creases
Authors: Parque Victor , Miyashita Tomoyuki 
Published: November 2022

Abstract
Spiral folding of flat and planar membranes with finite thickness is of relevant interest to develop the spin-type deployable membrane structures for space environments and for consumer applications. Examples involve the design and development of origami-based structures, airbags, antenna design, wrapping of food by thin membranes, wheel design, and membrane deployment for medical applications. In this paper, we propose the governing equations to fold planar membranes with finite thickness by using curved creases, whose governing equations render fold patterns whose radius of curvature tends to increase linearly by accommodating membrane thickness. The consideration of curvature along in the crease patterns is relevant and potential to balance the tension of outer layers with the compression of inner layers, and to distribute the out-of plane and localized bending near the creases and vertices. We present the mathematical formulations that consider the curved creases and describe folding examples of a planar membrane with a defined thickness. Our computational experiments have shown (1) the versatility to model a plural number of curvature profiles, and (2) the feasibility of global deployment by using the compliant and explicit numerical simulations. From viewpoints of configuration and deployment performance, the curved crease patterns are potential to extend the versatility and smoothness of spiral folding mechanisms.
On the Computation of the Average of Spatial Displacements
Authors: Ge Qiaode Jeffrey , Yu Zihan , Arbab Mona , Langer Mark 
Published: November 2022

Abstract
Many applications in biomechanics and medical imaging call for the analysis of the kinematic errors in a group of patients statistically using the average displacement and the standard deviations from the average. This paper studies the problem of computing the average displacement from a set of given spatial displacements using three types of parametric representations: Euler angles and translation vectors, unit quaternions and translation vectors, and dual quaternions. It has been shown that the use of Euclidean norm in the space of unit quaternions reduces the problem to that of computing the average for each quaternion component separately and independently. While the resulting algorithm is simple, the change of the sign of a unit quaternion could lead to an incorrect result. A novel kinematic measure based on dual quaternions is introduced to capture the separation between two spatial displacement. This kinematic measure is then used to formulate a constrained least squares minimization problem. It has been shown that the problem decomposes into that of finding the optimal translation vector and the optimal unit quaternion. The former is simply the centroid of the set of given translation vectors and the latter can be obtained as the eigenvector corresponding to the least eigenvalue of a 4 × 4 positive definite symmetric matrix. It is found that the weight factor used in combining rotations and translations in the formulation does not play a role in the final outcome. Examples are provided to show the comparisons of these methods.
ShapOrator: Enabling Design Iteration for Young Designers Through Shape Verbalization
Authors: Vyas Shantanu , Chen Ting-Ju , Woodward Jay , Krishnamurthy Vinayak R. 
Published: November 2022

Abstract
We investigate speech-based input as a means to enable reflective thinking for younger individuals (middle- and high-school students) during design iterations. Verbalization offers a unique way to externalize ideas in early design and could therefore lead to new pathways for exploration and iteration, especially for K-12 students who possess the creative potential but are not technically trained in the design process. Interactive design systems, however, by-and-large utilize sketching, multi-touch, and gestural inputs. As a result, (1) there is little know-how regarding how to operationalize verbal inputs as a meaningful way to facilitate idea exploration and (2) there is little fundamental understanding of the underlying cognitive mechanisms for iteration through verbal communication. We take the initial steps towards these gaps by first designing and implementing the ShapOrator interface that takes verbal descriptions of geometric parameters (shape, size, instances) in a semi-natural language form and determines the appropriate transformations to a given design artifact modeled as a shape assembly. Using ShapOrator as our experimental setup we conducted an in-depth observational study on 10 middle- and high-school students tasked with designing spaceships. Our study revealed that participants were able to create a variety of designs while associating functional and topical contexts to their spaceships throughout the design iteration process.
A Study on Hexapod Gait Adaptation by Enumerative Encoding and Particle Swarm Optimization
Authors: Parque Victor 
Published: November 2022

Abstract
Adapting to actuator failures is relevant robotic systems to continuously perform tasks such as exploration and mapping of unknown environments. This paper studies the adaptation ability to faulty hexapod legs by using an enumerative encoding scheme of the gaits locomotion strategy. The computational studies using the feasible set of leg failures through a physics-enabled simulation environment show (1) the feasibility of using the factoradic representation to explore feasible hexapod gait recoveries, and (2) the effectiveness of using an exploitative particle swarm-based heuristic to find feasible recovery strategies with minimal deviation to pre-defined locomotion commands under a small number of objective function evaluations. The results has the potential to further explore the enumerative encoding scheme and population-based optimization heuristics to render feasible hexapod gaits when actuators become malfunction on the field.
Framing Evolving Market Structures Using a Business Model Canvas
Authors: Starks Jacob , Rai Chandra , Devegowda Deepak , Allen Janet K. , Mistree Farrokh 
Published: November 2022

Abstract
As climate change makes it essential for the industry to move away from fossil fuels it is important to reconceptualize the entire system of energy production and distribution. In engineering design practice we focus on creating solutions and designs that may be highly effective and efficient without taking into account evolving market structures. We hypothesize that to realize evolving market structures, engineering design needs to be policy-driven and facilitate the monetization of investment by industry, and equitable social return on investment for the government and community.
There is interest in transitioning to a low carbon hydrogen economy. There is a considerable body of work on making green hydrogen production cost-effective while also creating useful forms of carbon. There is little work done, however, on modeling the storage and distribution services for at-scale hydrogen deployment and cross-disciplinary modeling of technologies and services to enable an effective transition. In essence, current translation research is limited by an underlying assumption that the only obstacle to hydrogen adoption is achieving cost competitiveness, which disregards the roles that stakeholders (government, industry, and community) may play in enabling or hindering a transition.
In this paper, we present an approach to identifying policies for transitioning to a low carbon hydrogen economy from a business (market structure) perspective. This involves framing a design problem for an evolving market from a policy-driven perspective. We use the business model canvas as the foundational framework to map the activities and services required to effectively supply resources and satisfy the demand to identify gaps in provided services and potential bottlenecks in transition or integration. We demonstrate this potential by using the business model canvas to identify a way forward in transitioning to a new market structure for a low carbon hydrogen economy.
Design and Development of a Sit-To-Stand Device Using A Variational Autoencoder-Based Deep Neural Network
Authors: Lyu Zhijie , Purwar Anurag 
Published: November 2022

Abstract
This work brings together rigid body kinematics with machine learning to present a mechanism synthesis pipeline for design and development of a Sit-to-Stand (STS) device. Practical device design problems require multiple constraints to be satisfied simultaneously. Most of the focus in the past has been on satisfying the key functional requirements presented as a path or motion generation problem and being content with a handful of solutions obtained. We present a new design pipeline, which begins with effective and compact data generation, to leveraging a deep neural network for representation of coupler curves and mechanism parameters, and finally ending with new metrics for quantitative evaluation of design constraints and rank ordering design concepts. This framework is capable of generating a large number of plausible solutions while meeting design constraints. As an example, we present many single-degree-of-freedom six-bar mechanisms that satisfy the given constraints and are ranked-ordered on the basis of the metric. While the focus of this paper is on the design of STS motion for integration in a multi-functional mobility assist device, this approach is broadly applicable to device design problems in other areas as well.
Incorporating Truck-Drone Bimodal Delivery System Into Mobile Additive Manufacturing Considering Preferred Delivery Time-Window and Optimal Printing Sequence
Authors: Ma Junfeng 
Published: November 2022

Abstract
Additive manufacturing technology is one of the leading technologies of the latest phase of the industrial revolution, Industry 4.0, and is attracting significant attention from both academia and industries. Truck-drone bimodal delivery system was studied and applied for multiple decades due to its high cost-savings and high customer satisfaction. However, to the best of our knowledge, there is no prior work combining additive manufacturing and truck-drone delivery system, although each of them has been widely implemented. This paper aims to fill this gap by integrating truck-drone delivery system with mobile additive manufacturing while also considering the customers’ preferred delivery time-window and the optimal printing sequence. A mixed integer linear programming model is proposed to establish this innovative mechanism. A computational case study was applied to validate the proposed model. The results confirm the applicability and effectiveness of the proposed model. The results also indicate that the maximum drone flight range and the printing job complexity have the significant impacts on the overall cost performance and satisfying the customers’ on-time delivery requirements. The proposed mechanism is applicable to multiple industrial sectors, including manufacturing, after-sales service, and warehouse inventory management.
Direct Torque Control of Electric Current Phase and Frequency in the Permanent-Magnet Synchronous Generator
Authors: Chumacero Erik , Akundi Aditya 
Published: November 2022

Abstract
The control design, formal stability analysis, and simulation results of a direct-torque controller applied to the permanent magnet synchronous generator (PMSG) is presented here. The controlled variables are the PMSG’s phase, amplitude, and frequency of the alternating current (AC) signal. For control design purposes and computer simulation, the PMSG is modeled in the dq frame of reference. On the other hand, the control algorithm is designed via backstepping technique and Lyapunov asymptotic stability is demonstrated for tracking error of the mechanical velocity and the electrical current. Uniform asymptotic stability is proved in a twofold procedure. First, it is shown that both mechanical and electrical subsystems of the PMSG are input to state stable with respect to conveniently selected inputs. Second, uniform asymptotic stability of the interconnected mechanical and electrical subsystems is shown via Lyapunov’s stability direct method. Finally, the performance of the closed-loop system, composed of the PMSG model and the control algorithm, is tested via numerical simulations, which show that the three-phase electric currents in the PMSG and the rotor’s mechanical velocity track the imposed reference signals.
Relationships Among Band Tension, Sensor Pressure, Patient Comfort, and Puslatile Signal Quality for Wrist Worn Health Monitoring Devices
Authors: Naylor Thomas , Black Roger , Hernandez Cameron , Jensen Brian D. 
Published: November 2022

Abstract
This paper presents the design and testing of a wrist worn health sensing band used to gather relationship data among band tension, sensor pressure, patient comfort, and measured pulsatile signal quality. It uses micromachined carbon-infiltrated carbon nanotube electrodes to detect a patient’s pulse using a bioimpedance approach. The micromachined electrodes experience no corrosion, and they are both strongly conductive and hypoallergenic. A simple mathematical model was developed to show the relationship between pressure on the wrist and tension in the wristband. The wristband was tested by being worn by 10 different research subjects over 15 tests. During each test, the tension in the band was varied, and the tension, pressure, and bioimpedance signal were measured and recorded. The test subject also reported a comfort and pain level score for each level of band tension. The results show that the model correctly predicts that tension varies linearly with pressure, and that the pressure vs. tension slope increases with increasing wrist width. There also exists a linear relationship between tension and patient pain/comfort, but pressure does not show an effect on the patient discomfort or pain experienced. Signal quality when measured in the range of 0–4 N of tension and 0–20 kPa of sensor pressure does not have a direct correlation to either tension or pressure.