Sounak Chakrabarti
Papers
1
Total Citations
34
H-Index
1
About
Sounak Chakrabarti is a leading researcher in human-robot interaction, with a focus on enabling intuitive communication between people and autonomous systems. His work bridges robotics, haptics, and augmented reality to solve a fundamental challenge: how can robots transparently convey what they have learned from human guidance? In his highly cited 2021 paper, “Communicating Inferred Goals with Passive Augmented Reality and Active Haptic Feedback” (34 citations), Chakrabarti introduces a novel framework that combines passive visual cues from augmented reality with active haptic feedback to let humans know what their robot has inferred during teleoperation. This dual-modality approach allows assistive robot arms to share their internal goal estimates in real time, making collaborative tasks more efficient and trustworthy. By addressing the critical “what does the robot think I want?” gap, Chakrabarti’s work has significant implications for assistive robotics, rehabilitation, and shared autonomy. His research is widely recognized for its practical impact on human-robot teamwork, earning citations from scholars in robotics, AI, and human factors engineering. Chakrabarti continues to push the boundaries of how robots can learn from and communicate with people, making him a key voice in the future of intuitive human-robot collaboration.
Research Focus
Key Achievements
Top Papers
- 1