ERGOBOSS: Ergonomic Optimization of Body-Supporting Surfaces
IEEE Transactions on Visualization and Computer Graphics 2021
People
- Danyong Zhao
University of Southern California - Yijing Li
University of Southern California - Siddhartha Chaudhuri
Adobe Research - Timothy Langlois
Adobe Research - Jernej Barbič
University of Southern California
Project material
Citation
-
Danyong Zhao, Yijing Li, Siddhartha Chaudhuri, Timothy Langlois, Jernej Barbič:
ERGOBOSS: Ergonomic Optimization of Body-Supporting Surfaces, IEEE Transactions on Visualization & Computer Graphics, 28(12), 2022 BIBTEX
Abstract
Humans routinely sit or lean against supporting surfaces and it is important to shape these surfaces to be comfortable and ergonomic. We give a method to design the geometric shape of rigid supporting surfaces to maximize the ergonomics of physically based contact between the surface and a deformable human. We model the soft deformable human using a layer of FEM deformable tissue surrounding a rigid core, with measured realistic elastic material properties, and large-deformation nonlinear analysis. We define a novel cost function to measure the ergonomics of contact between the human and the supporting surface. We give a stable and computationally efficient contact model that is differentiable with respect to the supporting surface shape. This makes it possible to optimize our ergonomic cost function using gradient-based optimizers. Our optimizer produces supporting surfaces superior to prior work on ergonomic shape design. Our examples include furniture, apparel and tools. We also validate our results by scanning a real human subject's foot and optimizing a shoe sole shape to maximize foot contact ergonomics. We 3D-print the optimized shoe sole, measure contact pressure using pressure sensors, and demonstrate that the real unoptimized and optimized pressure distributions qualitatively match those predicted by our simulation.
Comments, questions to Jernej Barbič.
Funding
- NSF (IIS-1911224)
- Bosch Research
- USC Annerberg Graduate Fellowship
- Adobe Research
Disclaimer
Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.
Copyright notice
The documents contained in these directories are included by the contributing authors as a means to ensure timely dissemination of scholarly and technical work on a non-commercial basis. Copyright and all rights therein are maintained by the authors or by other copyright holders, notwithstanding that they have offered their works here electronically. It is understood that all persons copying this information will adhere to the terms and constraints invoked by each author's copyright. These works may not be reposted without the explicit permission of the copyright holder.
Unique accesses: