Biography

Martin Nisser is an Assistant Professor of Aeronautics and Astronautics at the University of Washington, where his main research interests are in computational fabrication and assembly. He completed his PhD at MIT in the Computer Science and Artificial Intelligence Laboratory. Previously, he completed his masters and undergraduate degrees at MIT, ETH Zurich, and The University of Edinburgh, and held intern or staff appointments at the Boston Dynamics A.I. Institute, Tesla Motors, Harvard University and the European Space Agency. He is a Sweden-America fellow, a Bernard Gold fellow, and has appeared in media including BBC News, The NBC Daily Show, The Washington Post, NASA TV, Forbes and Popular Science.

Education

• PhD Computer Science, MIT
• S.M. Computer Science, MIT
• MSc Robotics, Systems & Control, ETH Zurich
• BEng Mechanical Engineering, University of Edinburgh

Research Statement

In my lab's work on digital manufacturing, we co-develop hardware and software to create computational fabrication and assembly platforms for use at points-of-need. We're interested in developing in situ digital fabrication platforms that can autonomously manufacture artefacts not suited to traditional mass manufacturing. For applications spanning in-space assembly to personal fabrication, a need for artefact diversity at low volumes intersects with logistical constraints and limited manufacturing expertise to challenge the typical efficiencies of centralized mass manufacturing. Personal fabrication platforms such as 3D printers epitomize the potential for in situ manufacturing to rapidly create custom artefacts in hospitals, community hubs, and other points-of-need, but significant challenges remain to achieving their full utility. Our research vision is to enable on-demand manufacturing of customized artefacts in the places they are needed, while supporting their design by the people who need them. A key strategy to this research is to develop new platforms that enable situ fabrication in the constrained space environment, and to incubate these technologies for new applications in automated assembly on Earth. To do so, we leverage principles from self-assembly and robotics to co-develop software and hardware platforms that automate fabrication of structures and machines at the point-of-need, uncoupling manufacturing expertise from manufacturing processes. In software, we create platforms that support the design of custom 3D geometries that draw on computational techniques for depositing, folding, and assembling material into target shapes. While in hardware, we anchor these algorithms to physical constraints on power and mechanics to develop machines and materials that can fabricate and assemble physical artefacts. Combined, we use these methods to create systems that can assemble structures in space, autonomously fabricate robots, and digitally program materials for self-assembly.

Current projects

Generative Design Tools for End User Manufacturing

Generative design tools are today emerging that can empower end users themselves to custom-design 3D objects. However, irregularities in the generated design files prevent small-scale manufacturers from producing them using techniques like 3D printing. In this project, we seek to identify key challenges facing the manufacturability of AI-generated designs and to develop new software tools that address them.

Hybrid Manufacturing for Robotics
Building functional devices, such as robots, is a today manual and difficult process that requires recruiting a number of disparate manufacturing processes, from 3D printing to PCB assembly. In this project, we are hybridizing manufacturing techniques to create new multi-process fabrication machines that can automate the production of customized robots and other electromechanical devices.

Select publications

1. Martin Nisser, Christina Chen Liao, Yuchen Chai, Aradhana Adhikari, Steve Hodges, Stefanie Mueller, "LaserFactory: An Electromechanical Assembly and Fabrication Platform Integrated with a Laser Cutter to make Functional Devices and Robots", In Proceedings of CHI 2021.
2. Martin Nisser, Leon Cheng, Yashaswini Makaram, Ryo Suzuki, Stefanie Mueller. "ElectroVoxel: Electromagnetically Actuated Pivoting for Scalable Modular Self-Reconfigurable Robots", In Proceedings of ICRA 2022.
3. Martin Nisser, Yashaswini Makaram, Faraz Faruqi, Ryo Suzuki, Stefanie Mueller. "Selective Self-Assembly using Re-Programmable Magnetic Pixels", In Proceedings of IROS 2022.

News