Taizoon Chunawala — 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 ↗

2025

Safety-Critical and Distributed Nonlinear Predictive Controllers for Teams of Quadrupedal Robots

Basit Muhammad Imran, Jeeseop Kim, Taizoon Chunawala, Alexander Leonessa, Kaveh Akbari Hamed

RA-L 2025

This paper presents a novel hierarchical, safety-critical control framework that integrates distributed nonlinear model predictive controllers (DNMPCs) with control barrier functions (CBFs) to enable cooperative locomotion of multi-agent quadrupedal robots in complex environments. While NMPC-based m

Cited by 4 Source ↗Scholar ↗

2024

Predictive Control With Indirect Adaptive Laws for Payload Transportation by Quadrupedal Robots

Leila Amanzadeh, Taizoon Chunawala, Randall T. Fawcett, Alexander Leonessa, Kaveh Akbari Hamed

RA-L 2024

This letter formally develops a novel hierarchical planning and control framework for robust payload transportation by quadrupedal robots, integrating a model predictive control (MPC) algorithm with a gradient-descent-based adaptive updating law. At the framework's high level, an indirect adaptive l

Cited by 13 Source ↗Scholar ↗