Mohit Srinivasan
Papers
6
Total Citations
126
H-Index
5
About
Mohit Srinivasan is a leading researcher in the control and coordination of multi-agent and multi-robot systems, with a particular focus on ensuring safety and complex task execution. His work masterfully bridges formal methods, control theory, and machine learning. A central contribution is the development and application of **control barrier functions (CBFs)** for safety-critical systems. He pioneered the concept of **finite-time control barrier functions**, which guarantee that a system converges to a safe set within a specified time, and has extended this to handle complex temporal logic specifications, allowing robots to follow intricate, time-sensitive instructions while remaining safe. His highly cited 2018 paper (85 citations) on this topic is a cornerstone of the field. Srinivasan also tackles the computational challenges of multi-robot coordination, notably by using **imitation learning to accelerate mixed-integer programming** for motion planning, a method that dramatically speeds up real-time decision-making. His work on **extent-compatible CBFs** and **weighted polar CBFs** provides elegant, practical solutions for controlling robots with non-trivial shapes and dynamics, such as unicycles. Through this impactful portfolio, Srinivasan is shaping the future of autonomous, safe, and coordinated multi-robot teams.
Research Focus
Key Achievements
Top Papers
- 1
- 2Extent-compatible control barrier functions14 citations · 2021
- 3
- 4
- 5A Sequential Composition Framework for Coordinating Multirobot Behaviors6 citations · 2020
- 6