Sampada Deglurkar
Papers
2
Total Citations
10
H-Index
2
About
Sampada Deglurkar is a robotics researcher whose work sits at the intersection of motion planning, human-robot interaction, and real-time safety assurance. Her research tackles a fundamental challenge in autonomous navigation: how to make robots that can move safely and efficiently in dynamic, human-filled environments without sacrificing computational speed for safety guarantees. In her highly cited paper "A Scalable Framework For Real-Time Multi-Robot, Multi-Human Collision Avoidance" (2019, 6 citations), Deglurkar introduced a novel framework that enables robots to navigate robustly among multiple moving agents, including humans, addressing a critical gap in existing motion planning algorithms. Her earlier work, "Planning, Fast and Slow: A Framework for Adaptive Real-Time Safe Trajectory Planning" (2018, 4 citations), proposed an elegant hybrid approach that balances computationally efficient planning with strong safety guarantees—a concept inspired by cognitive science that has resonated with the robotics community. Deglurkar's contributions are particularly notable for their practical focus on scalability and real-world deployment, making her research valuable for applications ranging from warehouse automation to assistive robotics.
Research Focus
Key Achievements
Top Papers
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- 2