Suman Pal
Papers
1
Total Citations
12
H-Index
1
About
Suman Pal is a roboticist and human-robot interaction researcher whose work focuses on enabling robots to learn complex tasks through natural, intuitive interaction with humans. His primary research areas include interactive task learning, behavior tree representations, and learning from demonstration. Pal’s most significant contribution is developing methods for robots to learn behavior trees—a modular and interpretable task representation—directly from imperfect human demonstrations. His 2023 paper on interactively learning behavior trees from imperfect human demonstrations (12 citations) addresses a critical challenge in robotics: how non-expert users can teach robots new skills without programming knowledge. This work bridges the gap between human teaching and robot learning, making robotic systems more accessible and adaptable. Pal’s research has implications for collaborative manufacturing, assistive robotics, and domestic service robots, where flexible, user-friendly task learning is essential. By focusing on robustness to human error and natural interaction, his work advances the practical deployment of learning robots in real-world settings.
Research Focus
Key Achievements
Top Papers
- 1Interactively learning behavior trees from imperfect human demonstrations12 citations · 2023