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Research on Cooperative Motion of Mobile Robots Based on Nonlinear Model Predictive Control

Author(s)

Tingting Zhang

Affiliation(s)

College of Intelligent Manufacturing, Chongqing Industry & Trade Polytechnic, Chongqing, China

Abstract

For mobile robots in collaborative tasks, the coordinated control of mobile base and manipulator suffers from decoupling difficulties. Meanwhile, motion planning in high-dimensional spaces requires considerable computation. This paper proposes a coordinated motion control scheme for mobile manipulators based on nonlinear model predictive control (NMPC), which enables stable coordinated motion between the mobile base and manipulator. The complete kinematic model of the mobile robot is established, and an NMPC-based coordinated controller is designed. A simulation model is built in Simulink and CoppeliaSim. The optimal control trajectory is calculated by minimizing the given objective function, and the proposed scheme is verified in simulation environments. The results show that the mobile base and manipulator can work coordinately. When the end-effector moves at 0.5 m/s, 1.0 m/s and 1.5 m/s, its average tracking error is between 4.63 cm and 14.87 cm, and the average tracking error of the mobile base ranges from 4.18 cm to 12.53 cm.

Keywords

Mobile Robot; Mobile Manipulator Coordination; Trajectory Tracking; NMPC

References

[1]Lu Z, Wang Y. A differentiable dynamic modeling approach to integrated motion planning and actuator physical design for mobile manipulators. Journal of Field Robotics, 2025, 42(1): 37–64. [2]Gao S, Zhu Y, et al. Motion-force control of mobile manipulators via extended uncertainty and disturbance estimation. Control Engineering Practice, 2026, 167: 106650. [3]Sun P Y, Li J, Liu Y F, et. al. Compliant Door-opening Technology for Mobile Manipulator Based on Platform-manipulator Collaboration Strategy. Robot, 2026, 48(1): 102-115. [4]Wu C, Wang R, Song M, et al. Real-time whole-body motion planning for mobile manipulators using environment-adaptive search and spatial-temporal optimization. IEEE International Conference on Robotics and Automation. 2024. [5]Qin D, Wu J, Liu A, et al. Cooperation and coordination transportation for nonholonomic mobile manipulators: A distributed model predictive control approach. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2023, 53(2): 848–860. [6]Du X T, Zhou S Q, Schoellig AP. Hierarchical task model predictive control for sequential mobile manipulation tasks. IEEE Robotics and Automation Letters, 2024, 9(2): 1270–1277. [7]Geng M. Research on Mobile Grasping Problem of Composite Robot Based on Hierarchical Cooperative Control. Yanshan University, 2025. [8]Liu C, Qin T. Motion control of four-wheel distributed drive mobile robot based on MPC, 2025, (5): 6-12. [9]Kashi Z, Yadegar M, Meskin N, et al. Safe model predictive control of a non-holonomic mobile manipulator under multiple constraints using control barrier functions. IEEE Access, 2025, 13: 76638–76653. [10]Liu S, Wang F, Li B L. Simulation of Robot Trajectory Tracking Control under Nonholonomic Constraints. Computer Simulation, 2023, 40(10): 422-425+444. [11]Wang Y, Chen R, Zhao M. Whole-body model predictive control for mobile manipulation with task priority transition. IEEE International Conference on Robotics and Automation. 2025. Shen W, Hu Y, Liu Y, et al. Holistic model predictive control for mobile manipulation. IEEE International Conference on Automation Science and Engineering. 2026.