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Eugeni L. Doubrovski

dblp:204/9386 · DBLP profile ↗
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5ranked-venue papers
1as first author
1since 2021 · last 2021
0000-0003-2785-3452ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Graphics, computer vision, multimedia, augmented reality and games · 4 · 1 first-author · 1 since 2021Artificial intelligence and machine learning · 1Systems, architecture and hardware · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer graphics and multimedia
3 papers
Computational fabrication · 89% Computer animation and physical simulation · 8% Geometric modeling and processing · 3%
Artificial intelligence
1 paper
Robot manipulation · 100%

Topics — the 5 heaviest of 8, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computational fabrication › textile fabrication
knitting
0.512021
Knitting 4D garments with elasticity controlled for body motion · ACM Trans. Graph. 2021
Computational fabrication › additive manufacturing
fused deposition modeling
0.412020
A Framework for Adaptive Width Control of Dense Contour-Parallel Toolpaths in Fused Deposition Modeling · Comput. Aided Des. 2020
Computational fabrication
tool path generation
0.412020
A Framework for Adaptive Width Control of Dense Contour-Parallel Toolpaths in Fused Deposition Modeling · Comput. Aided Des. 2020
Robotics › Robot manipulation
soft robotics
0.312018
Color-Based Sensing of Bending Deformation on Soft Robots · ICRA 2018
Computational fabrication
additive manufacturing
0.112020
A Framework for Adaptive Width Control of Dense Contour-Parallel Toolpaths in Fused Deposition Modeling · Comput. Aided Des. 2020

Methods — techniques the papers use, named apart from their topics

tiling algorithm · 0.5physics-based computation · 0.5graph-based stitch mesh algorithm · 0.5statistical validation · 0.4back pressure compensation · 0.4color-based sensing · 0.33d printing · 0.3voxel-based fabrication · 0.2
YearPublicationVenuePosition
2021 Knitting 4D garments with elasticity controlled for body motion
abstract
In this paper, we present a new computational pipeline for designing and fabricating 4D garments as knitwear that considers comfort during body movement. This is achieved by careful control of elasticity distribution to reduce uncomfortable pressure and unwanted sliding caused by body motion. We exploit the ability to knit patterns in different elastic levels by single-jersey jacquard (SJJ) with two yarns. We design the distribution of elasticity for a garment by physics-based computation, the optimized elasticity on the garment is then converted into instructions for a digital knitting machine by two algorithms proposed in this paper. Specifically, a graph-based algorithm is proposed to generate knittable stitch meshes that can accurately capture the 3D shape of a garment, and a tiling algorithm is employed to assign SJJ patterns on the stitch mesh to realize the designed distribution of elasticity. The effectiveness of our approach is verified on simulation results and on specimens physically fabricated by knitting machines.
Xingjian Han, Xiangjia Chen, Yukun Lai, Eugeni L. Doubrovski, Emily Whiting, Charlie C. L. Wang
ACM Trans. Graph.6
2020 A Framework for Adaptive Width Control of Dense Contour-Parallel Toolpaths in Fused Deposition Modeling
abstract
3D printing techniques such as Fused Deposition Modeling (FDM) have enabled the fabrication of complex geometry quickly and cheaply. Objects are produced by filling (a portion of) the 2D polygons of consecutive layers with contour-parallel extrusion toolpaths. Uniform width toolpaths consisting of inward offsets from the outline polygons produce over- and underfill regions in the center of the shape, which are especially detrimental to the mechanical performance of thin parts. In order to fill shapes with arbitrary diameter densely the toolpaths require adaptive width. Existing approaches for generating toolpaths with adaptive width result in a large variation in widths, which for some hardware systems is difficult to realize accurately. In this paper we present a framework which supports multiple schemes to generate toolpaths with adaptive width, by employing a function to decide the number of beads and their widths. Furthermore, we propose a novel scheme which reduces extreme bead widths, while limiting the number of altered toolpaths. We statistically validate the effectiveness of our framework and this novel scheme on a data set of representative 3D models, and physically validate it by developing a technique, called back pressure compensation, for off-the-shelf FDM systems to effectively realize adaptive width.
Tim Kuipers, Eugeni L. Doubrovski, Jun Wu 0005, Charlie C. L. Wang
Comput. Aided Des.2
2018 Color-Based Sensing of Bending Deformation on Soft Robots
abstract
This paper introduces a novel approach for sensing the bending deformation on soft robots by leveraging multicolor 3D printing. The measurement of deformation enables to complete the feedback loop of deformation control on soft actuators. The working principle of our approach is based on using compact color sensors to detect deformation that is visualized by the change of color ratios. Two novel designs are presented to generate color signals on 3D printed objects, which we call an external signal generator and an internal signal generator. Signal processing and calibration methods are developed to transform the raw RGB-data into a meaningful deformation metric. Our experimental tests taken on soft pneumatic actuators verify that color signals can be stably generated and captured to indicate the bending deformation. The results also demonstrate the usability of this sensing approach in deformation control.
Rob B. N. Scharff, Rens M. Doornbusch, Xander L. Klootwijk, Ajinkya A. Doshi, Eugeni L. Doubrovski, Jun Wu 0005, J. M. P. Geraedts, Charlie C. L. Wang
ICRA5
2018 Hatching for 3D prints: Line-based halftoning for dual extrusion fused deposition modeling
abstract
This work presents a halftoning technique to manufacture 3D objects with the appearance of continuous grayscale imagery for Fused Deposition Modeling (FDM) printers. While droplet-based dithering is a common halftoning technique, this is not applicable to FDM printing, since FDM builds up objects by extruding material in semi-continuous paths. The line-based halftoning principle called ‘hatching’ is applied to the line patterns naturally occurring in FDM prints, which are built up in a layer-by-layer fashion. The proposed halftoning technique is not limited by the challenges existing techniques face; existing FDM coloring techniques greatly influence the surface geometry and deteriorate with surface slopes deviating from vertical or greatly influence the basic parameters of the printing process and thereby the structural properties of the resulting product. Furthermore, the proposed technique has little effect on printing time. Experiments on a dual-nozzle FDM printer show promising results. Future work is required to calibrate the perceived tone.
Tim Kuipers, Willemijn S. Elkhuizen, Jouke C. Verlinden, Eugeni L. Doubrovski
Comput. Graph.4
2015 Voxel-based fabrication through material property mapping: A design method for bitmap printing
Eugeni L. Doubrovski, E. Y. Tsai, D. Dikovsky, J. M. P. Geraedts, Hugh M. Herr, Neri Oxman
Comput. Aided Des.1