Amrish Baskaran

University of Maryland, College Park

Papers

2

Total Citations

20

H-Index

2

About

Amrish Baskaran is a leading researcher in multi-agent robotics, specializing in persistent monitoring and reinforcement learning. His work addresses the fundamental challenge of coordinating teams of robots to continuously observe dynamic environments, where each robot is constrained by a limited, obstacle-obstructed field-of-view—such as a camera in a cluttered space. Baskaran’s major contribution lies in formulating the Visibility-based Persistent Monitoring (VPM) problem and developing multi-agent reinforcement learning (MARL) frameworks to solve it. His 2021 paper on this topic, with 16 citations, introduces algorithms that enable robots to autonomously learn coordinated trajectories, ensuring no area remains unmonitored for extended periods. This builds on his earlier 2020 work on persistent monitoring, which laid the groundwork for scalable, decentralized control in complex environments. Baskaran’s research has significant implications for applications like surveillance, environmental monitoring, and disaster response, where reliable, long-term observation is critical. By combining theoretical rigor with practical MARL solutions, he has established himself as a key innovator in autonomous systems, advancing the frontier of how multiple robots can intelligently share sensing tasks.

Research Focus

Key Achievements

2
H-Index
2
Papers
20
Total Citations
10
Avg Citations/Paper
🏆 Most Cited Paper
Multi-Agent Reinforcement Learning for Visibility-based Persistent Monitoring
16 citations · 2021
📈 Most Prolific Year: 2021 (1 Papers)
🤝 Key Collaborators: 3
🏛 Institutions: University of Maryland, College Park

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
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