Papers
5
Total Citations
22
H-Index
3
About
Manan Tayal is an emerging robotics researcher whose work spans autonomous navigation, safety-critical control systems, and bipedal locomotion. His most significant contributions center on Control Barrier Functions (CBFs) for collision avoidance, where he has pioneered the integration of collision cone geometry into CBF frameworks — a novel approach enabling unmanned ground and aerial vehicles to proactively avoid both static and kinematic obstacles in real time. His 2024 papers on Collision Cone CBFs and Polygonal Cone CBFs (PolyC2BF) have already garnered over 16 combined citations, demonstrating rapid uptake within the robotics community, particularly for applications in cluttered and confined environments such as search-and-rescue and mining operations. Beyond navigation safety, Tayal has made meaningful contributions to bipedal robotics through the Stoch BiRo platform — a low-cost, modular robot designed for uneven terrain — and BiRoDiff, a diffusion policy framework enabling robust locomotion on unseen terrains. Together, these works reflect a research philosophy that bridges theoretical rigor with accessible, experimentally validated hardware. Tayal's output positions him as a promising contributor to both safe autonomy and legged robot locomotion fields.
Research Focus
Key Achievements
Top Papers
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- 3A Collision Cone Approach for Control Barrier Functions4 citations · 2024
- 4
- 5Stoch BiRo: Design and Control of a Low-Cost Bipedal Robot3 citations · 2024