Sanket Kalwar
Papers
1
Total Citations
5
H-Index
1
About
Sanket Kalwar is a roboticist specializing in dexterous manipulation and grasp planning for complex, real-world environments. His research focuses on the intersection of geometric deep learning and dual-arm robotic systems, aiming to give robots the spatial intelligence to handle unstructured objects. In his highly cited 2024 work, "Constrained 6-DoF Grasp Generation on Complex Shapes for Improved Dual-Arm Manipulation," Kalwar tackles the critical challenge of generating stable, region-specific grasp poses for objects with intricate geometries—a task essential for bimanual coordination. By leveraging a deep understanding of local surface geometry, his method enables robots to efficiently identify viable contact points on complex shapes, directly improving the reliability of dual-arm manipulation tasks. This contribution is foundational for advancing robotic assembly, logistics, and human-robot collaboration. With his work accumulating early citations, Kalwar is establishing himself as a key voice in the next generation of robotic grasping, pushing the field beyond simple parallel-jaw grips toward truly adaptive, whole-hand manipulation.
Research Focus
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Top Papers
- 1