Devansh R. Agrawal
Papers
6
Total Citations
72
H-Index
4
About
Devansh R. Agrawal is a rising leader in safe autonomy and information-driven robotics, whose work bridges rigorous control theory with practical multi-robot systems. His primary research areas include control barrier functions (CBFs) for safety-critical control, ergodic search for persistent environmental monitoring, and sensor-based planning under uncertainty. Agrawal’s most impactful contribution is his comprehensive 2024 tutorial on advances in CBF theory (43 citations), which addresses real-world challenges such as time-varying safety constraints and input limits—providing a foundational resource for the safe control of autonomous and robotic systems. He also introduced the concept of *clarity*, an information-theoretic measure for dynamic coverage and informative path planning, and developed the ECLARES framework for energy-aware ergodic search, enabling long-duration missions under battery constraints. His constructive method for designing safe multirate controllers for differentially-flat systems further demonstrates his ability to translate theoretical guarantees into deployable architectures. With over 70 total citations and a growing portfolio of work in top venues, Agrawal is shaping how robots safely explore, monitor, and interact with complex environments.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3Eclares: Energy-Aware Clarity-Driven Ergodic Search6 citations · 2024
- 4
- 5
- 6