Papers
10
Total Citations
82
H-Index
5
About
Ravi Pandya’s research lies at the intersection of human-robot interaction, safe control, and learning for small-scale robotics. His most cited work, “Learning Image-Conditioned Dynamics Models for Control of Underactuated Legged Millirobots” (26 citations), pioneered data-driven control for highly dynamic, small-scale robots, enabling them to navigate complex environments with improved obstacle scaling. Pandya has also made significant contributions to ergonomic and safe human-robot collaboration. In “Learning Human Ergonomic Preferences for Handovers” (23 citations), he developed methods for robots to hand over objects in ways that minimize human strain, directly improving physical comfort in assistive settings. His work on “Safe and Efficient Exploration of Human Models During Human-Robot Interaction” (7 citations) addresses the critical challenge of robots learning accurate human models while maintaining safety—a foundational problem for deploying autonomous systems in shared spaces. More recently, Pandya has explored proactive collaboration and explainability, as seen in “Towards Proactive Safe Human-Robot Collaborations via Data-Efficient Conditional Behavior Prediction” and “Multi-Agent Strategy Explanations for Human-Robot Collaboration.” With over 80 total citations, his research is shaping how robots can learn from, adapt to, and safely coordinate with people in real-world environments.
Research Focus
Key Achievements
Top Papers
- 1
- 2Learning Human Ergonomic Preferences for Handovers23 citations · 2018
- 3
- 4Nonverbal Robot Feedback for Human Teachers7 citations · 2019
- 5
- 6Multi-Agent Strategy Explanations for Human-Robot Collaboration5 citations · 2024
- 7
- 8Multimodal Safe Control for Human-Robot Interaction2 citations · 2024
- 9
- 10Multi-Agent Strategy Explanations for Human-Robot Collaboration2 citations · 2023