Aneesh Chauhan
Papers
11
Total Citations
194
H-Index
7
About
Aneesh Chauhan’s research lies at the intersection of robotics, artificial intelligence, and cognitive systems, with a primary focus on enabling robots to learn and interact with their environment through language. His most influential work, “How many words can my robot learn? An approach and experiments with one-class learning” (40 citations), pioneered methods for grounding object names in robotic perception, allowing robots to learn vocabulary through human instruction. Chauhan’s contributions extend to developing perceptual memory systems for semantic grounding in service robots (32 citations), where he addressed the critical challenge of anchoring abstract symbols to physical objects. His work on open-ended category learning (19 citations) and interactive teaching (22 citations) has been instrumental in creating robots capable of continuous, unsupervised knowledge acquisition. Notably, his recent research on robotics for quality-driven post-harvest supply chains (32 citations) demonstrates the practical application of his expertise, exploring soft-robotics solutions for handling delicate agricultural products. Chauhan’s comprehensive survey of commercial robotic arms (17 citations) has also become a valuable resource for researchers in manipulation. Through his decade-spanning work, Chauhan has established himself as a key figure in developing robots that can learn, adapt, and communicate effectively with humans in real-world settings.
Research Focus
Key Achievements
Top Papers
- 1
- 2Robotics for a Quality-Driven Post-harvest Supply Chain32 citations · 2022
- 3
- 4Using spoken words to guide open-ended category formation24 citations · 2011
- 5
- 6Open-ended category learning for language acquisition19 citations · 2008
- 7A brief survey of commercial robotic arms for research on manipulation17 citations · 2012
- 8
- 9Measuring the response of soft fruits to robotic handling2 citations · 2025
- 10