Khush Agrawal

Visvesvaraya National Institute of Technology

Papers

Total Citations

H-Index

About

Khush Agrawal is a robotics researcher whose work focuses on autonomous navigation and human-robot interaction, with particular emphasis on deep learning applications for mobile robots operating in complex environments. His major contributions include developing a novel deep learning-based approach for stair segmentation and behavioral cloning, enabling robots to autonomously climb stairs—a critical capability for urban search and rescue operations. This work, published in 2019, has garnered 7 citations and represents a significant advancement in making mobile robots more versatile for surveillance, military, and industrial applications. Agrawal also pioneered a multiplexed detection and tracking system for person-following robots, published in 2020 with 6 citations, which enhances robots' ability to maintain reliable human tracking in dynamic settings. His research addresses fundamental challenges in deploying robots in unstructured environments, combining computer vision, deep learning, and control systems to create more capable autonomous platforms. Agrawal's work has practical implications for emergency response, security, and industrial automation, demonstrating how intelligent perception systems can expand the operational envelope of mobile robots beyond flat, structured terrain.