Papers
7
Total Citations
177
H-Index
5
About
Aran Sena is a leading researcher in human-robot interaction, with a focus on making robots more intuitive and effective partners for people. His work centers on three key areas: interaction control for contact robots, learning from demonstration, and human-robot collaborative systems. Sena's major contributions include developing frameworks that allow robots to detect human intent during physical interaction, enabling safer and more responsive collaboration in contexts like rehabilitation and surgery. His highly cited 2022 review on interaction control (54 citations) has become a foundational resource for the field. Sena has also advanced robot learning by addressing the critical role of human teachers—his work on quantifying and improving teaching behavior in demonstration-based learning (47 and 16 citations) reveals that effective robot learning depends as much on training the human as the machine. Notably, his 2023 paper on human-robot collaborative surgery (33 citations) demonstrates how shared control can reduce surgeon workload in complex bimanual tasks like peg transfer. With additional contributions to teleoperation for time-delayed tasks and task-parameterised movement learning, Sena's research is shaping the future of assistive and collaborative robotics.
Research Focus
Key Achievements
Top Papers
- 1A review on interaction control for contact robots through intent detection54 citations · 2022
- 2Quantifying teaching behavior in robot learning from demonstration47 citations · 2019
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- 5Teaching Human Teachers to Teach Robot Learners16 citations · 2018
- 6Haptic Bimanual System for Teleoperation of Time-Delayed Tasks5 citations · 2021
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