K. B. Saxena

Kyushu Institute of Technology, Tata Consultancy Services (India)

Papers

Total Citations

H-Index

About

K. B. Saxena’s research lies at the intersection of robotic manipulation, human-robot collaboration, and AI-driven formulation design, with a particular focus on handling deformable objects like garments. His most impactful work, “Garment Recognition and Grasping Point Detection for Clothing Assistance Task using Deep Learning” (34 citations), addresses the fundamental challenge of robotic cloth manipulation—a task critical for assistive technologies in healthcare and daily living. By developing deep learning models to recognize garment states and identify optimal grasping points, Saxena has advanced the ability of robots to interact with highly deformable, non-linear materials. His work on human-robot collaboration for table-setting tasks (4 citations) further demonstrates his commitment to practical, real-world applications of robotics in domestic environments. In a notable departure, Saxena has also contributed to the formulated products industry, proposing an integrated “Generate, Make, and Test” framework using knowledge graphs to automate formulation design—a process traditionally reliant on expert intuition. This work highlights his versatility in applying AI to both physical manipulation and chemical product development. Through these contributions, Saxena is shaping the future of assistive robotics and intelligent automation.