Manikantan Nambi

About

Manikantan Nambi is a leading researcher in robotic manipulation, with a focus on advancing automation in warehouse logistics and precision surgical systems. His most impactful contribution is **ARMBench** (32 citations), a large-scale, object-centric benchmark dataset that has become a foundational resource for robotic manipulation in unstructured warehouse environments. This work addresses the critical challenge of enabling robotic manipulators to handle a vast diversity of objects, setting a new standard for evaluating manipulation algorithms. Nambi has also made significant strides in human-robot collaboration, particularly in admittance-type devices used for precise tasks. His research on human force control (13 citations) and velocity control with scaled visual feedback (4 citations) has deepened our understanding of how operators interact with nonbackdrivable robotic systems. In the domain of medical robotics, he explored telemanipulated retinal surgery (4 citations), investigating the impact of haptic-interface kinematics on novice user performance. Through these contributions, Nambi bridges fundamental human-robot interaction studies with practical, high-impact applications in industry and medicine.

Research Focus

Key Achievements

Top Papers

1. 1
   ARMBench: An Object-centric Benchmark Dataset for Robotic Manipulation

   32 citations · 2023
2. 2
   On the Ability of Humans to Apply Controlled Forces to Admittance-Type Devices

   13 citations · 2011
3. 3
   Effect of Haptic-Interface Virtual Kinematics on the Performance and Preference of Novice Users in Telemanipulated Retinal Surgery

   4 citations · 2016
4. 4
   Human Velocity Control of Admittance-Type Robotic Devices With Scaled Visual Feedback of Device Motion

   4 citations · 2016

Key Collaborators

Contact & Links