Sudeep Sarkar

University of South Florida, The Ohio State University

Papers

10

Total Citations

132

H-Index

7

About

Sudeep Sarkar’s research lies at the intersection of robotics, computer vision, and human-robot interaction, with a focus on enabling machines to perceive, explore, and manipulate their environments autonomously. He has made significant contributions to 3D shape recovery and pose estimation, notably through his work on multi-scale superquadric fitting for unknown objects (37 citations), which allows robotic systems to rapidly acquire geometric information from point cloud data for efficient manipulation. His pioneering work on exploring unknown polygonal environments with bounded visibility (26 citations) addresses fundamental challenges in autonomous navigation, developing online algorithms for robots to map and traverse complex, obstacle-filled spaces. Sarkar has also advanced telerobotic systems by integrating intention recognition, enabling robots to identify and assist human operators in grasping tasks based on real-time motion cues (22 citations). His earlier work on dynamic edge warping for recovering disparity maps from uncalibrated stereo images (9 citations) laid groundwork for robust 3D perception under weak constraints. With a career spanning decades, Sarkar’s research has profoundly impacted autonomous robotics, from foundational exploration algorithms to practical grasping and teleoperation systems.

Research Focus

Key Achievements

7
H-Index
10
Papers
132
Total Citations
13
Avg Citations/Paper
🏆 Most Cited Paper
Multi-scale superquadric fitting for efficient shape and pose recovery of unknown objects
37 citations · 2013
📈 Most Prolific Year: 2014 (2 Papers)
🤝 Key Collaborators: 15
🏛 Institutions: University of South Florida, The Ohio State University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago