Jenna Parrillo
Papers
3
Total Citations
57
H-Index
3
About
Jenna Parrillo is a leading researcher in human–robot collaboration, with a primary focus on improving how robots communicate their intent and internal states to human partners in shared workspaces. Her most influential work, "Methods for Expressing Robot Intent for Human–Robot Collaboration in Shared Workspaces" (2021, 34 citations), investigates user-tested strategies for making robot actions more predictable and transparent, directly addressing a critical bottleneck in industrial human–robot teams. Parrillo further advanced the field by demonstrating how projection mapping can externalize a robot’s perception results and action intent directly onto the environment, offering a more salient and accurate alternative to traditional non-verbal cues like eye gaze or arm movement. Her contributions extend to mobile manipulation challenges, where she tackled complex, confined environments with irregular objects, as showcased in her work on the FetchIt! Challenge (2020, 18 citations). By bridging the gap between a robot’s internal reasoning and human understanding, Parrillo’s research has laid essential groundwork for safer, more intuitive human–robot interaction in manufacturing and beyond.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3