Nav: Home

Carpentry Compiler helps woodworkers design objects that they can actually make

December 02, 2019

As the holidays approach, people might be thinking of neat do-it-yourself woodworking projects to give as gifts. But there's often a disconnect between designing an object and coming up with the best way to make it.

Now researchers at the University of Washington have created Carpentry Compiler, a digital tool that allows users to design woodworking projects. Once a project is designed, the tool creates optimized fabrication instructions based on the materials and equipment a user has available. The team presented this research Nov. 19 at SIGGRAPH Asia in Brisbane, Australia.

"To make a good design, you need to think about how it will be made," said senior author Adriana Schulz, an assistant professor in the Paul G. Allen School of Computer Science & Engineering. "Then we have this very difficult problem of optimizing the fabrication instructions while we are also optimizing the design. But if you think of both design and fabrication as programs, you can use methods from programming languages to solve problems in carpentry, which is really cool."

For Carpentry Compiler, the researchers created a system called Hardware Extensible Languages for Manufacturing, or HELM. HELM is composed of two different programming languages: a high-level language for designing an object, and then a low-level language for the fabrication instructions.

"Say I want to make a piece of wood that's cut at a 45-degree angle," Schulz said. "In the design user interface, I create a box and then I draw a line where I want the cut to be and tell the computer 'Remove this part.' That's the high-level language. Then the low-level language says 'Take a two-by-four, take your chop saw, set up your chop saw for a 45-degree angle, align the lumber to your chop saw and chop.'"

As the user designs an object using the high-level language, which looks similar to standard CAD software, a compiler verifies that the design is possible based on what tools and materials the user has specified they have. Once the user is finished designing, the compiler comes up with a set of optimal fabrication instructions based on different costs.

"If you want to make a bookcase, it will give you multiple plans to make it," Schulz said. "One might use less material. Another one might be more precise because it uses a more precise tool. And a third one is faster, but it uses more material. All these plans make the same bookcase, but they are not identical in terms of cost. These are examples of tradeoffs that a designer could explore."

The compiler has to sift through a huge space of possible combinations of instructions to find the best ones. But if it treats fabrication instructions like a program, then it can use programming tricks to simplify its search and select promising candidates.

"One program might have a good way to make the edge of the table; another one finds a good way to make the legs," said co-author Zachary Tatlock, an associate professor in the Allen School. "And we can find those and recombine them to make the best overall plan."

Currently Carpentry Compiler is optimizing fabrication plans based on fabrication time and precision. In the future, the team would like it to take into account grain orientation and uncertainty in using specific types of tools. From there, the team hopes to expand this idea to more complex projects -- such as a project that requires woodworking and 3D printing.

"The future of manufacturing is about being able to create diverse, customizable high-performing parts," Schulz said. "Previous revolutions have been about productivity mostly. But now it's about what we can make. And who can make it."
-end-
Additional co-authors are Chenming Wu, a doctoral student at Tsinghua University who completed this research as a visiting student at the UW; Haisen Zhao, a postdoctoral research associate in the Allen School; Chandrakana Nandi, a doctoral student in the Allen School; and Jeffrey Lipton, an assistant professor in the UW's mechanical engineering department. This research was funded by the National Science Foundation, an Adobe Research fellowship and a Tsinghua scholarship for overseas graduate students.

For more information, contact Schulz at adriana@cs.washington.edu.

University of Washington

Related Computer Articles:

Stabilizing brain-computer interfaces
Researchers from Carnegie Mellon University (CMU) and the University of Pittsburgh (Pitt) have published research in Nature Biomedical Engineering that will drastically improve brain-computer interfaces and their ability to remain stabilized during use, greatly reducing or potentially eliminating the need to recalibrate these devices during or between experiments.
Computer-generated genomes
Professor Beat Christen, ETH Zurich to speak in the AAAS 2020 session, 'Synthetic Biology: Digital Design of Living Systems.' Christen will describe how computational algorithms paired with chemical DNA synthesis enable digital manufacturing of biological systems up to the size of entire microbial genomes.
Computer-based weather forecast: New algorithm outperforms mainframe computer systems
The exponential growth in computer processing power seen over the past 60 years may soon come to a halt.
A computer that understands how you feel
Neuroscientists have developed a brain-inspired computer system that can look at an image and determine what emotion it evokes in people.
Computer program looks five minutes into the future
Scientists from the University of Bonn have developed software that can look minutes into the future: The program learns the typical sequence of actions, such as cooking, from video sequences.
Computer redesigns enzyme
University of Groningen biotechnologists used a computational method to redesign aspartase and convert it to a catalyst for asymmetric hydroamination reactions.
Mining for gold with a computer
Engineers from Texas A&M University and Virginia Tech report important new insights into nanoporous gold -- a material with growing applications in several areas, including energy storage and biomedical devices -- all without stepping into a lab.
Teaching quantum physics to a computer
An international collaboration led by ETH physicists has used machine learning to teach a computer how to predict the outcomes of quantum experiments.
Seeing the next dimension of computer chips
Japanese researchers used a scanning tunneling microscope to image the side-surfaces of 3-D silicon crystals for the first time.
How old does your computer think you are?
Computerised face recognition is an important part of initiatives to develop security systems, in building social networks, in curating photographs, and many other applications.
More Computer News and Computer Current Events

Trending Science News

Current Coronavirus (COVID-19) News

Top Science Podcasts

We have hand picked the top science podcasts of 2020.
Now Playing: TED Radio Hour

Making Amends
What makes a true apology? What does it mean to make amends for past mistakes? This hour, TED speakers explore how repairing the wrongs of the past is the first step toward healing for the future. Guests include historian and preservationist Brent Leggs, law professor Martha Minow, librarian Dawn Wacek, and playwright V (formerly Eve Ensler).
Now Playing: Science for the People

#566 Is Your Gut Leaking?
This week we're busting the human gut wide open with Dr. Alessio Fasano from the Center for Celiac Research and Treatment at Massachusetts General Hospital. Join host Anika Hazra for our discussion separating fact from fiction on the controversial topic of leaky gut syndrome. We cover everything from what causes a leaky gut to interpreting the results of a gut microbiome test! Related links: Center for Celiac Research and Treatment website and their YouTube channel
Now Playing: Radiolab

The Third. A TED Talk.
Jad gives a TED talk about his life as a journalist and how Radiolab has evolved over the years. Here's how TED described it:How do you end a story? Host of Radiolab Jad Abumrad tells how his search for an answer led him home to the mountains of Tennessee, where he met an unexpected teacher: Dolly Parton.Jad Nicholas Abumrad is a Lebanese-American radio host, composer and producer. He is the founder of the syndicated public radio program Radiolab, which is broadcast on over 600 radio stations nationwide and is downloaded more than 120 million times a year as a podcast. He also created More Perfect, a podcast that tells the stories behind the Supreme Court's most famous decisions. And most recently, Dolly Parton's America, a nine-episode podcast exploring the life and times of the iconic country music star. Abumrad has received three Peabody Awards and was named a MacArthur Fellow in 2011.