Award Abstract # 1526249
CHS: Small: Interactive Haptic Assembly and Docking for 3D Shapes

NSF Org: IIS
Division of Information & Intelligent Systems
Recipient: UNIVERSITY OF CONNECTICUT
Initial Amendment Date: August 19, 2015
Latest Amendment Date: July 13, 2020
Award Number: 1526249
Award Instrument: Standard Grant
Program Manager: Ephraim Glinert
IIS
 Division of Information & Intelligent Systems
CSE
 Directorate for Computer and Information Science and Engineering
Start Date: September 1, 2015
End Date: August 31, 2021 (Estimated)
Total Intended Award Amount: $497,499.00
Total Awarded Amount to Date: $497,499.00
Funds Obligated to Date: FY 2015 = $497,499.00
History of Investigator:
  • Horea Ilies (Principal Investigator)
    horea.ilies@uconn.edu
Recipient Sponsored Research Office: University of Connecticut
438 WHITNEY RD EXTENSION UNIT 1133
STORRS
CT  US  06269-9018
(860)486-3622
Sponsor Congressional District: 02
Primary Place of Performance: University of Connecticut
191 Auditorium Rd
Storrs
CT  US  06269-1133
Primary Place of Performance
Congressional District:
02
Unique Entity Identifier (UEI): WNTPS995QBM7
Parent UEI:
NSF Program(s): HCC-Human-Centered Computing
Primary Program Source: 01001516DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 7367, 7923
Program Element Code(s): 736700
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.070

ABSTRACT

Haptic human-computer interaction mechanisms and systems play a critical role in a variety of engineering and scientific activities that rely on the fundamental task of virtual object assembly, from protein docking, drug design and tele-surgery, to advanced manufacturing, rehabilitation, robotics, teleoperation and consumer applications. One of the key long-standing challenges in developing such practical interactive systems is the lack of a proper formulation of the guidance forces that effectively assist the user in the exploration of the virtual environment, from repulsing collisions to attracting proper contact. A secondary difficulty is that of achieving an efficient implementation that can maintain an acceptable haptic refresh rate. Current state-of-the art solutions to these open problems have been developed for severely restricted classes of shapes and motions, and rely heavily on heuristics that exploit drastic geometric limitations. To address these issues, the PI's goal of this research is to develop a purely geometric model for an artificial energy field that favors spatial relations leading to proper assembly of arbitrarily complex shapes. Project outcomes will lead to effective interaction mechanisms for intelligent human-computer or human-robot systems and will open the doors to the development of generic and fully automated assembly planners while simultaneously unlocking new levels of expression and productivity in activities that rely on interactive assembly tasks in a broad range of industrial, scientific and consumer applications, in domains as diverse as 3D user interfaces, engineering, and medical and assistive technologies. The PI's industrial partnerships will facilitate aggressive and widespread technology transfer.

To these ends, the energy function is expressed in terms of a convolution of shape-dependent affinity fields that rely on the novel concept of a space-continuous, well-defined, and robust density function, called the Skeletal Density Functions (SDF), whose sublevel sets in the limit are related to an implicit definition of the medial axis. Importantly, the proposed energy field leads to the first practical and automatic approach to detect key features that contribute to proper alignment or assembly, as well as the geometric constraints required for virtual assembly. Moreover, the proposed approach completely avoids the heuristic recipes and manual intervention that are common to existing methods for haptic assembly. The PI's preliminary results show that this research can unify the two haptic interaction phases of free motion and precision assembly, which are common in current haptic simulations, into a single interaction mode, and suggest a generic and automatic constraint model for the so-called virtual fixtures, with no restrictive assumption on the types of the assembly features and shapes involved.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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(Showing: 1 - 10 of 11)
Chen, Jiangce and Ilies, Horea T "Maximal Disjoint Ball Decompositions for shape modeling and analysis" Computer-Aided Design , v.126 , 2020 , p.102850 10.1016/j.cad.2020.102850
Jiangce Chen, Horea T Ilies "Maximal Disjoint Ball Decompositions for shape modeling and analysis" Computer-Aided Design , v.126 , 2020
M. Behzadi and H. Ilies "Real-Time Topology Optimization in 3D via Deep Transfer Learning" Computer-Aided Design , v.135 , 2021 , p.103014
Meysam T. Chorsi, Eli J. Curry, Hamid T. Chorsi, Ritopa Das, Jeffrey Baroody, Prashant K. Purohit, Horea Ilies, and Thanh D. Nguyen "Piezoelectric Biomaterials for Sensors and Actuators" Advanced Materials , v.31 , 2019 , p.1802084 10.1002/adma.201802084
Meysam T Chorsi, Pouya Tavousi, Caitlyn Mundrane, Vitaliy Gorbatyuk, Kazem Kazerounian, Horea Ilies "Kinematic Design of Functional Nanoscale Mechanisms From Molecular Primitives" ournal of Micro-and Nano-Manufacturing , v.9 , 2021
Morad Behandish, Horea Ilies "Analytic methods for geometric modeling via spherical decomposition" Computer Aided Design , v.70 , 2016 , p.100
Pouya Tavousi, Kazem Kazerounian and Horea Ilies "Synthesizing Functional Mechanisms From a Link Soup" Journal of Mechanical Design , v.138 , 2016 , p.062303-1
Radu Corcodel and Horea Ilies "Printability Analysis in Additive Manufacturing" CAD and Applications , 2017
Reed Williams and Horea Ilies "Adaptive eigensystem truncation for spectral shape signatures" CAD and Applications , v.14 , 2017
Reed Williams and Horea Ilies "Practical Shape Analysis and Segmentation Methods for Point Cloud Models" Computer Aided Geometric Design. , v.67 , 2018 , p.97-120 doi.org/10.1016/j.cagd.2018.10.003
Xiaojun Zhao and Horea Ilies "Learned 3D Shape Descriptors for Classifying 3D Point Cloud Models" CAD and Applications , v.14 , 2016
(Showing: 1 - 10 of 11)

PROJECT OUTCOMES REPORT

Disclaimer

This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.

The major goal of this project was to develop a theoretical and computational framework to support effective interaction mechanisms via haptic feedback for proper virtual assembly of arbitrarily complex shapes for interactive human-computer or human-robot systems.

During this project we have developed a purely geometric model for an artificial energy field that favors spatial relations leading to proper assembly of arbitrarily complex 3D models. Importantly, the proposed energy field leads to the first practical and automatic approach to detect key ?features? that contribute to proper alignment or assembly, as well as the geometric constraints required for virtual assembly. Moreover, the proposed approach completely avoids the heuristic recipes and manual intervention that are common to existing methods for haptic assembly. The theoretical and algorithmic outcomes of this research allow the unification of the two haptic interaction phases of free motion and precision assembly, which are common in current haptic simulations, into a single interaction mode.

Moreover, we have discovered and formulated a novel geometric representation applicable to 3D models using any valid geometric representation. Our representation relies on a unique spherical decomposition of a given 3D shape, whose computation only requires the ability of a geometric representation to compute distance. We have shown that this decomposition fully supports novel metrics for shape similarity and goodness of fit needed in haptic interactions between complex 3D models, as well as feature recognition and model decomposition of models using any valid geometric representation.

The project has also provided invaluable professional development opportunities for a number of graduate and undergraduate student researchers participating in this project and led to a number of journal and conference publications as well as patent applications.


Last Modified: 09/01/2021
Modified by: Horea T Ilies

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