Sarah Elliott
University of Washington, Torch Technologies (United States)
Papers
6
Total Citations
114
H-Index
5
About
Dr. Sarah Elliott’s research bridges two transformative frontiers in robotics: making machines capable of physical household chores and democratizing computer science education through accessible robot programming. Her work is defined by a dual commitment to advancing manipulation algorithms and lowering the barrier to entry for K-12 students. In robotic cleaning, she pioneered a novel approach to dirt rearrangement planning, enabling a manipulator to move arbitrary configurations of debris to a goal region using learned transition models—a contribution that has garnered 24 citations. She further advanced this domain by developing methods for robots to learn generalizable surface cleaning actions from human demonstration (22 citations), addressing the practical challenge of tool manipulation for tasks like dusting and scrubbing. In confined environments such as shelves and fridges, Elliott’s research on push-and-pull manipulation with tools (17 citations) has expanded the graspable workspace of robotic arms. Equally impactful is her work in educational outreach: her 2017 paper on end-user robot-programming tools (30 citations) and the “RobotIST” system (17 citations) introduced tangible, situated programming blocks that allow novices to intuitively command robots by referencing real-world objects. Her museum installation, where visitors programmed a human-size robot to perform timed poses, exemplifies her ability to make complex robotics engaging and accessible. With over 100 total citations, Elliott stands as a leading voice in both practical service robotics and inclusive STEM education.
Research Focus
Key Achievements
Top Papers
- 1Computer Science Outreach with End-User Robot-Programming Tools30 citations · 2017
- 2
- 3Learning generalizable surface cleaning actions from demonstration22 citations · 2017
- 4
- 5RobotIST17 citations · 2018
- 6Programming robots at the museum4 citations · 2013