Papers
7
Total Citations
365
H-Index
5
About
Kashish Gupta’s research lies at the intersection of robotics, artificial intelligence, and advanced manufacturing, with a primary focus on enabling seamless human-robot collaboration (HRC) in industrial settings. His most influential work, a 2021 survey on robot learning strategies for HRC, has garnered 328 citations, establishing him as a key voice in the field. Gupta’s major contributions include developing a hierarchical, AI-powered communication framework that introduces naturalness into human-robot dialogue, addressing the complexity of real-world industrial environments through the lens of complexity theory. He has also advanced practical manufacturing applications, notably in aerospace, where his vision-based system for detecting wrinkles and boundaries in fiber products supports the automated production of Airbus A350 components. Additionally, his exploration of curriculum-based deep reinforcement learning offers adaptive solutions for autonomous decision-making, while his earlier work on time-optimal rendezvous planning for pick-and-place tasks demonstrates a long-standing commitment to efficient task sharing. Through these diverse contributions, Gupta bridges theoretical frameworks with tangible industrial solutions, making his research highly relevant for students and researchers interested in the future of intelligent, collaborative robotic systems.
Research Focus
Key Achievements
Top Papers
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- 6Time-optimal rendezvous planning for pick-and-place task sharing4 citations · 2002
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