Robotics Thesis Proposal
- Newell-Simon Hall
- Mauldin Auditorium 1305
- RUTA PARIMAL DESAI
- Ph.D. Student
- Robotics Institute
- Carnegie Mellon University
Computational Design Tools for Accessible Robotics
A grand vision in robotics is that of a future wherein robots are integrated in daily human life just as smart phones are today. Such pervasive integration of robots would greatly benefit from faster design and manufacturing of robots that cater to individual needs. However, robots of today often take years to be created by experts. To enable widespread adoption of robotic technologies, we wish to democratize the design process through computer-assisted tools that support rapid creation of robots by the people, for the people.
In recent years, the availability of affordable electronics such as Rasberry Pi, Arduino, and digital fabrication technologies such as 3D printing, laser-cutting is enabling rapid creation of smart devices. While the hardware platforms themselves are accessible to a wider audience, the design process is the part that's challenging. Almost anyone can follow step-by-step instructions from a manual, but making a unique design is difficult and time-consuming. To change this status quo, we present a suite of intuitive computational tools that enable the design of a broad class of devices with embedded electromechanical components that casual users might want to create.
In particular, we develop tools for designing physical structure, and behavior of robotic devices with various form factors and functionalities. Key strengths of our tools include encapsulation of necessary domain knowledge using parameterized models, and automation of tedious design steps using optimization techniques. With intuitive and visual interfaces, our tools support interactive user-in-the-loop design. We also investigate the utility of physics-based simulation and design space exploration in aiding user design. We validate our tools by fabricating various prototypes, and by conducting user studies with novices.
Stelian Coros (Co-chair)
James McCann (Co-chair)
Scott E. Hudson
Tovi Grossman (Autodesk Research)