Tanmay Randhavane
Papers
7
Total Citations
80
H-Index
5
About
Tanmay Randhavane is a robotics and human-robot interaction researcher whose work sits at the compelling intersection of social navigation, affective computing, and autonomous systems. His research focuses on developing intelligent algorithms that enable robots to navigate crowded environments with a deep understanding of human psychology and emotion. Randhavane's most significant contributions center on emotion-aware robot navigation, where he has pioneered systems that estimate pedestrians' time-varying emotional states using multimodal inputs — including facial expressions and movement trajectories — through a sophisticated blend of Bayesian inference, deep learning, and psychological models such as the Pleasure-Arousal-Dominance framework. His widely cited work on the "Emotionally Intelligent Robot" series (2019) demonstrates how incorporating emotional awareness measurably improves social navigation in real-world crowd settings. Beyond emotion, Randhavane has made notable strides in social invisibility for robots, applying psychological concepts like group entitativity to help autonomous systems move through crowds without triggering negative human reactions — a subtle but practically important challenge for deployment in public spaces. His earlier SocioSense system incorporated personality trait theory for long-term pedestrian path prediction. With cumulative citations across seven influential publications, Randhavane's work represents a meaningful bridge between robotics engineering and human behavioral science, offering a richer, more human-centered vision of autonomous navigation.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5
- 6
- 7