Papers
6
Total Citations
70
H-Index
5
About
Gavin Suddrey is a leading researcher at the intersection of human-robot interaction (HRI), robot self-efficacy, and natural language programming. His work fundamentally explores how non-expert users can teach and interact with robots, making advanced robotics more accessible. Suddrey’s major contributions include developing the **Robot Self-Efficacy Scale**, a validated tool for measuring an individual’s confidence in interacting with robots—a concept with over 21 citations that has become foundational for designing user-friendly robotic systems. He has pioneered methods for **learning and executing re-usable Behaviour Trees from natural language instruction** (19 citations), enabling robots to generalize tasks across different contexts. His research also extends to social robotics for wellbeing, including a pilot randomized controlled trial (8 citations) where a humanoid robot delivered brief wellbeing training sessions. Notably, Suddrey’s work on enabling the Pepper robot to provide automated, interactive laboratory tours (7 citations) demonstrates practical applications of mobile social robots. With a total of over 70 citations across his key publications, Suddrey’s contributions are shaping how robots learn from humans and how humans perceive robotic capabilities, directly impacting fields from healthcare to domestic assistance.
Research Focus
Key Achievements
Top Papers
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- 6A Software System for Human-Robot Interaction To Collect Research Data3 citations · 2020