Hello, my name is Jeeeun Kim, an assistant professor at Texas A&M Unversity
I am going to present OmniSoft, a design tool for softness by examples on behalf of my collaboration with Adobe Research and UCLA HCI Research
If you look around the world, there are more and more applications that are 3D printable
partly thanks to the online repositories that advanced designers and experts share a sophisticated 3D object
from medical devices to rehabilitation gears to even feminine items
But we all have certain concerns that 3D printing, especially with a low-cost FDM 3D printing, we can only 3D print rigid objects
even with such material limitations, that is given by plastics, there are ways to address these issues
with the expected mechanical behaviors, so called meta-materials
All these are 3D printable shoes but with a different purpose and so provide different comforts when it is worn
Metamaterial is a very common technique, the metamaterial composition is not only found in 3D printing domain
It is actually a very common fabricaiton method, to overcome limited materiality
mainly targetting at random deformation
how to this should be structured to behave in the way that they want the material to deform in a certain condition.
However, designers are expected to exactly know
thus, designers are expected to place small microstructures nearby
to plan these properties ahead of time
However, many of current computer-aided design systems, CAD tools, in the fabrication domain
have focused on the optimization of the 3D objects' geometry features so-called shape features
For end-users, parametric user interface with the graphical representations of the shape
has been championed as the most promising way of manipulating the shapes
Parametric UI is great for designing shapes but setting constraints of them, such as setting the deformations or setting properties, is not great
and the simulation does not propose how the end users can do these in an easier way.
This is some kind of parametric UI, if we design a parametric UI for the soft objects
So the users can adjust the non-visual features with some parameters
Thinking about the properties such as softness, which is the internal characteristics of the object
these are not interpretable by these values, that we call the parameters
how would you design a soft button with flexible materials?
what does softness level 9 mean to users with different user intentions?
what does the softness level 3 mean to the user?
Probably we can change this to a little more familiar representations to the user using the natural language
to the softness from the softest to hardest
to the deformability from easiest to hardest
However, again, this is a subjective feeling and there are only a limited number of expression
And also someone may expect the hardest button for as hard as metal
whereas the other may expect the hardest button as hard enough but pressable as the hard rubbery button and so forth.
Also in fact the information that the fabrication machine, the 3D printer, needs to know to fabricate that softness is different from users' language
There are numbers of factors and parameters that affect properties of physical 3D objects
This is one screenshot from cura
that we have to set to realize what type of property
the softness level can be achieved from different settings
We noticed that there's a communication gap between the user's expression and the machine's interpretation
Our solution here is for users, to remind their previous experiences of existing objects as inputs
and for machines, optimizing parameters to produce parameters list, such as right flow rate right infill density and right printing speed
that can be actually used to define internal density and print speed or many other things that affect the softness level
For example, you know how soft the dish scrubber is, and you know how stiff your shoe sole or tire is
Once you specify "Oh, this is the right softness that I want in my 3D object"
then we can generate the list of parameters to replicate that exact softness
so for example, from our user study, our user created a soft corner to the end of a furniture
and the user can specify where they want this softness should be
and to the top of a guitar so it doesn't hurt his thigh when the user plays the guitar
There was one quiz that I want to ask if I were live
how do you think the softness difference could be in these two examples, a makeup sponge and dish scrubber?
Actually the answer is that they are exactly same. But we didn't exclude these from the options of user design tool
then a person who might not be familiar with the makeup sponge can still refer to the dish scrubber
so he can use whatever he feels comfortable and familiar as an input object as a reference
So how can this be addressed? We propose a data-driven approach,
to interpret the users' expression and obtain characteristics of objects
using a common device that we chose to represent how the softness is measured
we know how much of force is required to deform the soft objects by pushing them
we obtained a commercial device from Amazon which around just $20-30
and we collected lots of everyday objects as examples, and using this device
we measured the softness of them, and exposed this softness reference to the user interface
and by those standard numbers, we tried 3D printing many samples by differentiating print parameters
and then saw how we can achieve that exact softness by borrowing these 3D printing parameters
By in the inverse function, we can predict what are the best printing settings
then we can guess from the database
Specified by the real-world object as a reference that we know the number from the database, we can retrieve the right settings
This is the actual device how we measured the softness which is called Shore A softness scale device
and through the many user studies, we realized that the way that different users perceive the softness is similar to the standard
What does that mean?
Once we measure the sofness of the object with softness 5, and measure the object with softness 90
then obviously softness 90 is stiffer and people think that is actually stiffer even from different perceptions
From the user study and many examples from our study participants
we learned that the designers think that the ability to customize property means actually customizability of functions
Here, one user designed child-safe furniture so baby doesn't hurt from the sharp corner of the table
and the other proposed an ergonomic couch and a bike saddle while the other designed a guitar that does not hurt his thigh
in practice, we can imagine a custom steering wheel that informs novice drivers of the best grip
and the personalized shoe that provides custom comfort while keeping the other global part rigid, such as heel
So what can we do by providing the softness as one another design factor beyond the shape?
We can let the user design a 3D printed facade for the blind users
to make flat home appliances tangible so that they can independently operate those functions
or tactile picture books for younger children so they can develop the emergent literacy skills through the interactive modalities
and we can also design soft grippers for robotics applications
so they can feel, think, and touch from the tangible books
and the many other examples that we can imagine
which as previously detached from the design tool
We brought softness as a design factor to the early design stage
so was only possible to adjust after completing the design
so we get rid of tedious iteration processes in case the users feel that the property does not meet in the end,
so they adjust parameters, 3D print, test, and again, adjust parameters, 3D print, test again and again and again.
Our contribution is threefold.
We quantified fabrication factors that affect the property of the 3D printed objects through many 3D printing parameters
We identified a relationship between human's subjective perception and fabricated properties using standard scales
We also provide a user interface and the list of the library of common everyday examples with standard scales
so that it can be applied to many different metamaterial properties for other techniques to make those properties available to the users
I was Jeeeun Kim from Texas A&M HCIed Lab.
This is work, Omnisoft: a design tool for softness by examples is from a collaboration among Texas A&M, Adobe, and UCLA
Thank you