Rohit Lal

Visvesvaraya National Institute of Technology

Papers

Total Citations

H-Index

About

Rohit Lal is a robotics researcher whose work focuses on the intersection of soft robotics, computer vision, and autonomous navigation. His primary research areas include origami-inspired robot design, 6DOF pose estimation, and person-following mobile robotics. Lal’s major contribution lies in addressing the challenge of shape-invariant pose estimation for flexible, shape-morphing robots—a critical gap in soft robotics. His paper "ScoopNet" introduces a novel pipeline for 6DOF pose estimation tailored to origami-inspired worm robots, enabling precise tracking despite continuous shape changes. This work has garnered 8 citations and is foundational for applications in medicine and engineering where soft robots must navigate unstructured environments. Additionally, Lal developed a person-following mobile robot using multiplexed detection and tracking, achieving robust real-time human-robot interaction with 6 citations. His research bridges the gap between soft robot mechanics and perception systems, advancing the autonomy of deformable robots. Lal’s achievements highlight his ability to tackle underexplored problems in robotics, making him a rising contributor to the field of soft and autonomous systems.