Aniket Shirsat
Papers
3
Total Citations
32
H-Index
2
About
Aniket Shirsat is a researcher advancing the frontiers of multi-robot systems and swarm intelligence. His work centers on the control, coordination, and consensus of robotic collectives, with a particular focus on mean-field approaches and probabilistic modeling. In his most-cited paper, "Controllability and Stabilization for Herding a Robotic Swarm Using a Leader: A Mean-Field Approach" (26 citations), Shirsat introduced a novel model for guiding a swarm of follower agents to a target distribution using a single leader. This work provides a rigorous control-theoretic framework for swarm herding, a problem with broad applications in environmental monitoring and search-and-rescue. He further contributed to decentralized multi-robot coordination with "Probabilistic Consensus on Feature Distribution for Multi-Robot Systems With Markovian Exploration Dynamics" (4 citations), which enables teams of robots to collectively reconstruct occupancy grid maps through consensus. Additionally, his work on "Decentralized Multi-target Tracking with Multiple Quadrotors using a PHD Filter" (2 citations) addresses the challenge of tracking multiple stationary targets in unknown environments. Shirsat’s research elegantly bridges theoretical control and practical robotics, offering scalable solutions for autonomous systems operating under uncertainty.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3