With modern 3D printing technology, creating a chess set has become remarkably straightforward. Despite being installed permanently, If someone intends to incorporate 3D-printed elements into a space – such as installing a customized footrest under a desk, for instance – the project’s complexity will escalate accordingly. The area must be accurately measured. The objects should then be scaled, printed at a separate location, and subsequently attached to their intended positions. While handheld 3D printers do indeed exist, their accuracy is limited by design, accompanied by a notable learning curve for users.
Researchers at the University of Washington have developed MobiPrint, a mobile 3D printer capable of mapping a room and printing objects directly onto surfaces. With their intuitive graphic interface, customers are empowered to craft bespoke designs for designated areas that have been meticulously mapped by the crew’s advanced robotics technology. The prototype, built onto a modified shopper vacuum robot, enables the addition of accessibility features, customizable dwellings, and innovative possibilities for a space.
The crew publicly presented their project on Tuesday, October Fifteen researchers gathered at the ACM Symposium on Consumer Interface Software and Technology in Pittsburgh.
Here’s the improved text:
“Digital fabrication, including 3D printing, has reached maturity in its current form,” said Daniel Campos Zamora, a Ph.D. student under the guidance of Paul G. Allen Faculty of Pc Science & Engineering. How do we further amplify its impact and broaden accessibility, breaking down barriers that prevent people from utilizing its full potential? How can we adapt the ambient conditions to accommodate diverse needs, seamlessly integrating accessibility features with stylistic flourishes?
The prototype system enables the addition of accessible features, mirroring tactile markers to enhance usability for individuals who are blind or have low vision. These signs would potentially display information, similar to textual content advising conference attendees where to go, or alerting them to potential risks such as staircases. In order to effectively bridge an uneven flooring transition, the installation of a ramp may be necessary. MobiPrint allows customers to design and produce personalized products, including intricate art pieces up to 3 inches in height, offering a high level of customization.
Prior to printing the object, MobiPrint navigates an indoor space independently, leveraging LiDAR technology to create a precise digital mapping. Using the crew’s custom design software, the map is seamlessly transformed into a highly responsive and intuitive interactive canvas. Consumers have the option to select a template from MobiPrint’s library, such as a cat food bowl, or create their own custom design. As the consumer selects a location on the map, they navigate the intuitive design interface to scale and precisely position their print job. Lastly, the robotic arm strikes the exact placement, printing the item instantaneously on the ground.
For printing, this design leverages a bioplastic commonly used in 3D printing, specifically PLA. Researchers aim to enhance MobiPrint by equipping it with the capability to retrieve printed objects and subsequently recycle the plastic material used in the printing process. Researchers are keen to investigate the possibilities of robots capable of printing on various surfaces, including tabletops, walls, and other outdoor environments, utilizing a range of materials such as concrete.
“I consider the needs of young people on bikes or my friends and family members in wheelchairs, who often struggle to access sidewalks with high curbs,” said Jon E. Froehlich, a professor within the esteemed Allen Faculty. Wouldn’t it be wonderful to utilize Daniel’s robotic system to build a ramp in the near future, despite its initial limitations of functioning only briefly? This could fundamentally transform how we design and use spaces.
As a co-author of this paper, Liang He, an assistant professor at Purdue College and former doctoral student in the Allen School, contributed to this research. The research underlying this analysis received funding from the National Science Foundation.
