Vidya Sumathy
Papers
2
Total Citations
4
H-Index
2
About
Vidya Sumathy is a rising researcher in autonomous systems, specializing in decentralized multi-agent reinforcement learning and multi-robot exploration. Her work addresses a critical challenge in real-world robotics: enabling teams of agents to collaboratively explore unknown environments when reliable communication infrastructure is absent. Sumathy’s major contributions include novel frameworks that integrate inter-agent communication-based action spaces with reinforcement learning, allowing robots to coordinate effectively despite limited connectivity. In her 2024 paper, she pioneered a decentralized approach that leverages proximity-based network characteristics to maintain collaboration, while her 2025 work introduces a density-based frontier search method that handles both static and dynamic obstacles. Though early in her career, with each of her most-cited papers accumulating 2 citations, these works represent foundational steps toward practical deployment in search and rescue operations—a domain where her algorithms could dramatically improve mission efficiency. Sumathy’s research bridges the gap between theoretical multi-agent systems and real-world constraints, positioning her as an emerging voice in the future of autonomous exploration and disaster response robotics.
Research Focus
Key Achievements
Top Papers
- 1
- 2