Shubham S. Kumbhar — accepted AI-conference papers

2025

Finite-Step Capturability and Recursive Feasibility for Bipedal Walking in Constrained Regions

Shubham S. Kumbhar, Abhijeet Mangesh Kulkarni, Ioannis Poulakakis

ICRA 2025

This paper presents a Model Predictive Control (MPC) formulation for bipedal footstep planning based on the Linear Inverted Pendulum (LIP) model, ensuring recursive feasibility when navigating restricted regions. The proposed approach incorporates capturability and introduces a new constraint that f

Cited by 1 Source ↗Scholar ↗

2025

MPC-QP-Based Control Framework for Compliant Behavior of Humanoid Robots in Physical Collaboration with Humans

Shubham S. Kumbhar, Panagiotis Artemiadis

ICRA 2025

We present a control framework specifically for physical human-humanoid collaboration involving the transportation and manipulation of heavy objects. Using this framework, the humanoid can exhibit desired levels of compliance with the object to be co-transported. This desired compliance is achieved

Cited by 1 Source ↗Scholar ↗