Sarah Elliot
Papers
1
Total Citations
9
H-Index
1
About
Sarah Elliot is a leading researcher in human-robot interaction and robotic manipulation, with a focus on integrating human perception into autonomous systems. Her most cited work, "Interactive scene segmentation for efficient human-in-the-loop robot manipulation" (2017, 9 citations), addresses a critical bottleneck in robotics: enabling machines to navigate cluttered, unpredictable environments. By pioneering a human-aided perception paradigm, Elliot developed methods that allow robots to dynamically query human input for scene segmentation, significantly improving manipulation accuracy in real-world settings. This contribution bridges the gap between fully autonomous systems and teleoperation, offering a scalable solution for tasks like warehouse sorting or assistive robotics. Her research has been recognized for advancing human-in-the-loop frameworks, with citations reflecting its foundational role in interactive perception. Elliot’s work continues to influence how robots collaborate with humans, making her a key figure in the evolution of safe, efficient, and adaptive robotic systems.
Research Focus
Key Achievements
Top Papers
- 1