# End-Effector Stabilization of a 10-DOF Mobile Manipulator using Nonlinear Model Predictive Control

arXiv: https://arxiv.org/abs/2103.13153 · HTML: https://mlsanity.com/paper/2103.13153/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 24 Mar 2021.

## Built on by (most cited first, 1 of 1)

- [Handling Sparse Rewards in Reinforcement Learning Using Model Predictive Control](https://mlsanity.com/paper/2210.01525/) (2022)

## Abstract (arXiv)

Motion control of mobile manipulators (a robotic arm mounted on a mobile base) can be challenging for complex tasks such as material and package handling. In this paper, a task-space stabilization controller based on Nonlinear Model Predictive Control (NMPC) is designed and implemented to a 10 Degrees of Freedom (DOF) mobile manipulator which consists of a 7-DOF robotic arm and a 3-DOF mobile base. The system model is based on kinematic models where the end-effector orientation is parameterized directly by a rotation matrix. The state and control constraints as well as singularity constraints are explicitly included in the NMPC formulation. The controller is tested using real-time simulations, which demonstrate high positioning accuracy with tractable computational cost.