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

Fuente: arXiv
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Main Authors: Sambhus, Ruturaj, Mehta, Kapi Ketan, Sadeghi, Ali MirMohammad, Imran, Basit Muhammad, Kim, Jeeseop, Chunawala, Taizoon, Pastore, Vittorio, Vijayan, Sujith, Hamed, Kaveh Akbari
Format: Preprint
Published: 2025
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author Sambhus, Ruturaj
Mehta, Kapi Ketan
Sadeghi, Ali MirMohammad
Imran, Basit Muhammad
Kim, Jeeseop
Chunawala, Taizoon
Pastore, Vittorio
Vijayan, Sujith
Hamed, Kaveh Akbari
author_facet Sambhus, Ruturaj
Mehta, Kapi Ketan
Sadeghi, Ali MirMohammad
Imran, Basit Muhammad
Kim, Jeeseop
Chunawala, Taizoon
Pastore, Vittorio
Vijayan, Sujith
Hamed, Kaveh Akbari
contents Model predictive control (MPC) combined with reduced-order template models has emerged as a powerful tool for trajectory optimization in dynamic legged locomotion. However, loco-manipulation tasks performed by legged robots introduce additional complexity, necessitating computationally efficient MPC algorithms capable of handling high-degree-of-freedom (DoF) models. This letter presents a computationally efficient nonlinear MPC (NMPC) framework tailored for loco-manipulation tasks of quadrupedal robots equipped with robotic manipulators whose dynamics are non-negligible relative to those of the quadruped. The proposed framework adopts a decomposition strategy that couples locomotion template models -- such as the single rigid body (SRB) model -- with a full-order dynamic model of the robotic manipulator for torque-level control. This decomposition enables efficient real-time solution of the NMPC problem in a receding horizon fashion at 60 Hz. The optimal state and input trajectories generated by the NMPC for locomotion are tracked by a low-level nonlinear whole-body controller (WBC) running at 500 Hz, while the optimal torque commands for the manipulator are directly applied. The layered control architecture is validated through extensive numerical simulations and hardware experiments on a 15-kg Unitree Go2 quadrupedal robot augmented with a 4.4-kg 4-DoF Kinova arm. Given that the Kinova arm dynamics are non-negligible relative to the Go2 base, the proposed NMPC framework demonstrates robust stability in performing diverse loco-manipulation tasks, effectively handling external disturbances, payload variations, and uneven terrain.
format Preprint
id arxiv_https___arxiv_org_abs_2507_22042
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle A Nonlinear MPC Framework for Loco-Manipulation of Quadrupedal Robots with Non-Negligible Manipulator Dynamics
Sambhus, Ruturaj
Mehta, Kapi Ketan
Sadeghi, Ali MirMohammad
Imran, Basit Muhammad
Kim, Jeeseop
Chunawala, Taizoon
Pastore, Vittorio
Vijayan, Sujith
Hamed, Kaveh Akbari
Robotics
Optimization and Control
Model predictive control (MPC) combined with reduced-order template models has emerged as a powerful tool for trajectory optimization in dynamic legged locomotion. However, loco-manipulation tasks performed by legged robots introduce additional complexity, necessitating computationally efficient MPC algorithms capable of handling high-degree-of-freedom (DoF) models. This letter presents a computationally efficient nonlinear MPC (NMPC) framework tailored for loco-manipulation tasks of quadrupedal robots equipped with robotic manipulators whose dynamics are non-negligible relative to those of the quadruped. The proposed framework adopts a decomposition strategy that couples locomotion template models -- such as the single rigid body (SRB) model -- with a full-order dynamic model of the robotic manipulator for torque-level control. This decomposition enables efficient real-time solution of the NMPC problem in a receding horizon fashion at 60 Hz. The optimal state and input trajectories generated by the NMPC for locomotion are tracked by a low-level nonlinear whole-body controller (WBC) running at 500 Hz, while the optimal torque commands for the manipulator are directly applied. The layered control architecture is validated through extensive numerical simulations and hardware experiments on a 15-kg Unitree Go2 quadrupedal robot augmented with a 4.4-kg 4-DoF Kinova arm. Given that the Kinova arm dynamics are non-negligible relative to the Go2 base, the proposed NMPC framework demonstrates robust stability in performing diverse loco-manipulation tasks, effectively handling external disturbances, payload variations, and uneven terrain.
title A Nonlinear MPC Framework for Loco-Manipulation of Quadrupedal Robots with Non-Negligible Manipulator Dynamics
topic Robotics
Optimization and Control
url https://arxiv.org/abs/2507.22042