Papers
6
Total Citations
93
H-Index
5
About
Satyajit Ambike’s research bridges the mechanics of human movement and robotic manipulation, with a focus on how the brain controls hand-object interactions. His major contributions lie in understanding the neural control of prehension—how we grasp and hold objects—by reconstructing referent coordinate and apparent stiffness trajectories during movement. This work, detailed in his most-cited paper (49 citations), provides a framework for modeling how the central nervous system stabilizes grasped objects. He has also advanced robotic path tracking by developing geometric and temporal control strategies for non-redundant manipulators, enabling precise trajectory tracking for planar and spatial paths. In human robotics, Ambike introduced soft-contact and wrench-based approaches to grasp planning, computing safety margins in human prehension (7 citations) and improving robotic grip reliability. His work on soft-contact models has practical implications for prosthetic design and rehabilitation. With a total of over 90 citations across his key papers, Ambike’s interdisciplinary approach—combining biomechanics, control theory, and robotics—offers valuable insights for students and researchers interested in motor control, human-robot interaction, and dexterous manipulation.
Research Focus
Key Achievements
Top Papers
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- 4A soft-contact model for computing safety margins in human prehension7 citations · 2017
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