Papers
17
Total Citations
292
H-Index
10
About
Nishanth Koganti is a leading researcher in assistive and service robotics, with a primary focus on robotic clothing assistance for elderly and disabled populations. His work addresses the critical challenge of real-time estimation of human-cloth topological relationships using depth sensors, a foundational problem for enabling robots to perform dressing tasks—an essential Activity of Daily Living. Koganti pioneered the use of Bayesian nonparametric learning and latent space modeling to capture cloth dynamics, achieving robust state estimation despite the inherent ambiguity of deformable materials. His highly cited framework for imitation learning in clothing assistance (49 citations) and his restocking system for retail automation (41 citations) demonstrate the breadth of his impact, spanning both caregiving and commercial applications. Notably, he has also explored adaptive motion generation for autonomous cleaning and virtual reality interfaces for learning from demonstrations, showcasing his versatility. With multiple papers accumulating over 20 citations each, Koganti’s contributions are shaping the future of service robots in aging societies, where worker shortages demand intelligent, compliant, and data-efficient robotic solutions.
Research Focus
Key Achievements
Top Papers
- 1A framework for robotic clothing assistance by imitation learning49 citations · 2019
- 2
- 3
- 4
- 5
- 6
- 7
- 8
- 9
- 10