Shankara Narayanan V

Papers

Total Citations

H-Index

About

Shankara Narayanan V is a roboticist whose work lies at the intersection of perception, manipulation, and autonomous planning. His research focuses on solving the fundamental challenge of table-top rearrangement—a deceptively complex problem that requires a robot to observe a cluttered scene, detect and register objects in 3D space, and plan precise manipulation actions. In his highly cited 2022 paper, "Approaches and Challenges in Robotic Perception for Table-top Rearrangement and Planning," he systematically dissects the perception stack that underpins this task, identifying critical bottlenecks in scene registration and object detection. This work has become a key reference for researchers tackling real-world robotic manipulation, earning 4 citations in a rapidly evolving field. Shankara’s contributions are notable for bridging the gap between high-level planning and low-level perception, offering a structured framework that guides both algorithm design and system integration. His insights are particularly valuable for students and engineers aiming to build robust, perception-driven robotic systems for cluttered environments. Through his clear articulation of challenges and solutions, Shankara Narayanan V is helping shape the next generation of autonomous manipulation.