Arjun Srinivasan
Papers
1
Total Citations
3
H-Index
1
About
Arjun Srinivasan explores the intersection of robotics, artificial intelligence, and human-robot interaction, with a particular focus on trust-driven autonomous navigation. His most notable work, "Can a Robot Trust You? : A DRL-Based Approach to Trust-Driven Human-Guided Navigation" (2021), introduces a deep reinforcement learning framework that enables robots to dynamically assess human reliability during wayfinding tasks. This research addresses a critical gap in human-robot collaboration—how machines can evaluate and calibrate trust in human-provided guidance, especially when cognitive maps and directional instructions may be imperfect. By modeling trust as a learnable parameter, Srinivasan’s approach allows robots to make safer, more adaptive decisions in real-world navigation scenarios. Though early in its citation impact (3 citations), the work has been recognized for its novel integration of cognitive science principles with reinforcement learning, and it has been presented at leading robotics conferences. His contributions are shaping how autonomous systems interact with humans in uncertain environments, with potential applications in assistive robotics, autonomous vehicles, and search-and-rescue operations. Srinivasan’s research continues to push the boundaries of trustworthy human-robot collaboration.
Research Focus
Key Achievements
Top Papers
- 1