Open Access Publications

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Open access publications by faculty, postdocs, and graduate students in the Department of Mechanical Engineering.


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Now showing 1 - 5 of 38
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    Online Self-Calibration for Visual-Inertial Navigation: Models, Analysis, and Degeneracy
    (IEEE Transactions on Robotics, 2023-06-07) Yang, Yulin; Geneva, Patrick; Zuo, Xingxing; Huang, Guoquan
    As sensor calibration plays an important role in visual-inertial sensor fusion, this article performs an in-depth investigation of online self-calibration for robust and accurate visual-inertial state estimation. To this end, we first conduct complete observability analysis for visual-inertial navigation systems (VINS) with full calibration of sensing parameters, including inertial measurement unit (IMU)/camera intrinsics and IMU-camera spatial-temporal extrinsic calibration, along with readout time of rolling shutter (RS) cameras (if used). We study different inertial model variants containing intrinsic parameters that encompass most commonly used models for low-cost inertial sensors. With these models, the observability analysis of linearized VINS with full sensor calibration is performed. Our analysis theoretically proves the intuition commonly assumed in the literature—that is, VINS with full sensor calibration has four unobservable directions, corresponding to the system's global yaw and position, while all sensor calibration parameters are observable given fully excited motions. Moreover, we, for the first time, identify degenerate motion primitives for IMU and camera intrinsic calibration, which, when combined, may produce complex degenerate motions. We compare the proposed online self-calibration on commonly used IMUs against the state-of-art offline calibration toolbox Kalibr, showing that the proposed system achieves better consistency and repeatability. Based on our analysis and experimental evaluations, we also offer practical guidelines to effectively perform online IMU-camera self-calibration in practice.
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    Visual accuracy dominates over haptic speed for state estimation of a partner during collaborative sensorimotor interactions
    (Journal of Neurophysiology, 2023-07-01) Lakesh, Rakshith; Sullivan, Seth R.; Germain, Laura St.; Roth, Adam M.; Calalo, Jan A.; Buggeln, John; Ngo, Truc; Marchhart, Vanessa R. F.; Carter, Michael J.; Cashaback, Joshua G. A.
    We routinely have physical interactions with others, whether it be handing someone a glass of water or jointly moving a heavy object together. These sensorimotor interactions between humans typically rely on visual feedback and haptic feedback. Recent single-participant studies have highlighted that the unique noise and time delays of each sense must be considered to estimate the state, such as the position and velocity, of one’s own movement. However, we know little about how visual feedback and haptic feedback are used to estimate the state of another person. Here, we tested how humans utilize visual feedback and haptic feedback to estimate the state of their partner during a collaborative sensorimotor task. Across two experiments, we show that visual feedback dominated haptic feedback during collaboration. Specifically, we found that visual feedback led to comparatively lower task-relevant movement variability, smoother collaborative movements, and faster trial completion times. We also developed an optimal feedback controller that considered the noise and time delays of both visual feedback and haptic feedback to estimate the state of a partner. This model was able to capture both lower task-relevant movement variability and smoother collaborative movements. Taken together, our empirical and modeling results support the idea that visual accuracy is more important than haptic speed to perform state estimation of a partner during collaboration. NEW & NOTEWORTHY Physical collaboration between two or more individuals involves both visual and haptic feedback. Here, we investigated how visual and haptic feedback is used to estimate the movements of a partner during a collaboration task. Our experimental and computational modeling results parsimoniously support the notion that greater visual accuracy is more important than faster yet noisier haptic feedback when estimating the state of a partner.
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    Carbon Additive Manufacturing with a Near-Replica “Green-to-Brown” Transformation
    (Advanced Materials, 2023-05-30) Zhang, Chunyan; Shi, Baohui; He, Jinlong; Zhou, Lyu; Park, Soyeon; Doshi, Sagar; Shang, Yuanyuan; Deng, Kaiyue; Giordano, Marc; Qi, Xiangjun; Cui, Shuang; Liu, Ling; Ni, Chaoying; Fu, Kun Kelvin
    Nanocomposites containing nanoscale materials offer exciting opportunities to encode nanoscale features into macroscale dimensions, which produces unprecedented impact in material design and application. However, conventional methods cannot process nanocomposites with a high particle loading, as well as nanocomposites with the ability to be tailored at multiple scales. A composite architected mesoscale process strategy that brings particle loading nanoscale materials combined with multiscale features including nanoscale manipulation, mesoscale architecture, and macroscale formation to create spatially programmed nanocomposites with high particle loading and multiscale tailorability is reported. The process features a low-shrinking (<10%) “green-to-brown” transformation, making a near-geometric replica of the 3D design to produce a “brown” part with full nanomaterials to allow further matrix infill. This demonstration includes additively manufactured carbon nanocomposites containing carbon nanotubes (CNTs) and thermoset epoxy, leading to multiscale CNTs tailorability, performance improvement, and 3D complex geometry feasibility. The process can produce nanomaterial-assembled architectures with 3D geometry and multiscale features and can incorporate a wide range of matrix materials, such as polymers, metals, and ceramics, to fabricate nanocomposites for new device structures and applications.
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    Extrusion-Based Additively Manufactured PAEK and PAEK/CF Polymer Composites Performance: Role of Process Parameters on Strength, Toughness and Deflection at Failure
    (Journal of Composites Science, 2023-04-11) Sharafi, S.; Santare, M. H.; Gerdes, J.; Advani, S. G.
    Poly aryl-ether-ketone (PAEK) belongs to a family of high-performance semicrystalline polymers exhibiting outstanding material properties at high temperatures, making them suitable candidates for metallic part replacement in different industries such as aviation, oil and gas, chemical, and biomedical. Fused filament fabrication is an additive manufacturing (AM) method that can be used to produce intricate PAEK and PAEK composite parts and to tailor their mechanical properties such as stiffness, strength and deflection at failure. In this work, we present a methodology to identify the layer design and process parameters that will have the highest potential to affect the mechanical properties of additively manufactured parts, using our previously developed multiscale modeling framework. Five samples for each of the ten identified process conditions were fabricated using a Roboze-Argo 500 version 2 with heated chamber and dual extruder nozzle. The manufactured PAEK and PAEK/carbon fiber samples were tested until failure in an Instron, using a video extensometer system. Each sample was prepared with a speckle pattern for post analysis using digital image correlation (DIC) to measure the strain and displacement over its entire surface. The raster angle and the presence of fibers had the largest influence on the mechanical properties of the AM manufactured parts, and the resulting properties were comparable to the mechanical properties of injection molded parts.
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    A traveler-centric mobility game: Efficiency and stability under rationality and prospect theory
    (PLOS ONE, 2023-05-05) Chremos, Ioannis Vasileios; Malikopoulos, Andreas A.
    In this paper, we study a routing and travel-mode choice problem for mobility systems with a multimodal transportation network as a “mobility game” with coupled action sets. We formulate an atomic routing game to focus on the travelers’ preferences and study the impact on the efficiency of the travelers’ behavioral decision-making under rationality and prospect theory. To control the innate inefficiencies, we introduce a mobility “pricing mechanism,” in which we model traffic congestion using linear cost functions while also considering the waiting times at different transport hubs. We show that the travelers’ selfish actions lead to a pure-strategy Nash equilibrium. We then perform a Price of Anarchy and Price of Stability analysis to establish that the mobility system’s inefficiencies remain relatively low and the social welfare at a NE remains close to the social optimum as the number of travelers increases. We deviate from the standard game-theoretic analysis of decision-making by extending our mobility game to capture the subjective behavior of travelers using prospect theory. Finally, we provide a detailed discussion of implementing our proposed mobility game.
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