Shubhankar Riswadkar
Papers
1
Total Citations
2
H-Index
1
About
Shubhankar Riswadkar is a robotics researcher advancing the frontier of adaptive robot control, with a primary focus on variable impedance learning and human-robot interaction. His most cited work, "Variable Impedance Learning Control with Faster Re-learning and Reduced Initial Errors in Re-perturbation for Robots Operating in Divergent Force Fields" (2023), addresses a critical challenge in modern robotics: enabling machines to dynamically adjust their mechanical stiffness and damping in unpredictable environments. Riswadkar’s key contribution lies in developing a control framework that allows robots to rapidly relearn impedance parameters after disturbances, significantly reducing initial errors during re-perturbation—a breakthrough for tasks requiring precision in divergent force fields. This work has direct implications for safer, more efficient collaborative robots in manufacturing and rehabilitation. With 2 citations to date, his research is gaining traction among scholars working on adaptive control systems. Riswadkar’s approach stands out for its focus on faster convergence and error minimization, offering a practical pathway toward robots that can seamlessly adapt to changing conditions without extensive retraining. His findings represent a meaningful step toward truly autonomous, physically interactive machines.
Research Focus
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Top Papers
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