Papers
6
Total Citations
75
H-Index
4
About
Bolun Dai is a robotics researcher whose work focuses on safety-critical control, autonomous navigation, and visual servoing. His primary contributions lie in the development of control barrier function (CBF) based approaches that enable robots to operate safely in complex, unstructured environments. Dai’s most cited paper, "Safe Navigation and Obstacle Avoidance Using Differentiable Optimization Based Control Barrier Functions" (2023, 37 citations), introduces a novel method for constructing CBFs through differentiable optimization, addressing a key challenge in robotic safety. He further extends this framework in "DiffOcclusion" (2024, 21 citations), which tackles occlusion-free visual servoing, and "Sailing Through Point Clouds" (2024, 10 citations), enabling safe navigation using point cloud data. His work on dynamic obstacle avoidance (2024–2025) and learning locomotion controllers via deep FBSDE (2021) demonstrates his versatility, spanning from theoretical foundations to practical implementations. With a growing citation record, Dai is establishing himself as a rising contributor to safe and adaptive robotic systems, making his research highly relevant for students and engineers working on real-world autonomy.
Research Focus
Key Achievements
Top Papers
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- 4Learning Locomotion Controllers for Walking Using Deep FBSDE4 citations · 2021
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