Ruturaj Sambhus

About

Ruturaj Sambhus is a robotics researcher whose work sits at the intersection of control theory and machine learning, with a particular focus on enabling safer, more adaptive physical human-robot interaction. His primary research areas include force control for series elastic actuators (SEAs), model-free deep reinforcement learning, and the development of robust control architectures for compliant robotic systems. In his most cited work, "Real-Time Model-Free Deep Reinforcement Learning for Force Control of a Series Elastic Actuator" (2023), Sambhus addresses a critical challenge in modern robotics: achieving stable, high-performance force control without relying on complex system models. While traditional model-based methods can be brittle and PID controllers prone to instability due to actuator nonlinearities, Sambhus demonstrates that deep reinforcement learning can learn effective, real-time force control policies directly from interaction data. This contribution is particularly valuable for applications like walking, lifting, and manipulation, where compliant actuation is essential. With 3 citations already, his work is gaining recognition among researchers seeking practical, data-driven alternatives to classical control. Sambhus’s research promises to make robots more resilient and capable in unstructured, real-world environments.

Research Focus

Key Achievements

Top Papers

1. 1
   Real-Time Model-Free Deep Reinforcement Learning for Force Control of a Series Elastic Actuator

   3 citations · 2023

Key Collaborators

Contact & Links