Ruturaj Sambhus — accepted AI-conference papers

2026

A Nonlinear MPC Framework for Loco-Manipulation of Quadrupedal Robots With Non-Negligible Manipulator Dynamics

Ruturaj Sambhus, Kapi Ketan Mehta, Ali MirMohammad Sadeghi, Basit Muhammad Imran, Jeeseop Kim, Taizoon Chunawala +3

RA-L 2026

Model predictive control (MPC) with reduced-order template models has proven effective for dynamic legged locomotion, but loco-manipulation introduces additional complexity requiring efficient algorithms for high-degree-of-freedom (DoF) systems. This letter presents a computationally efficient nonli

Cited by 3 Source ↗Scholar ↗

2023

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

Ruturaj Sambhus, Aydin Gokce, Stephen Welch, Connor W. Herron, Alexander Leonessa

IROS 2023poster

Many state-of-the-art robotic applications utilize series elastic actuators (SEAs) with closed-loop force control to achieve complex tasks such as walking, lifting, and manipulation. Model-free PID control methods are more prone to instability due to nonlinearities in the SEA where cascaded model-ba…

Cited by 2 Source ↗Scholar ↗