DQ-NMPC: Dual-Quaternion NMPC for Quadrotor Flight

2025-10-13

AI Summary

Agile flight control of quadrotors in complex dynamic environments is hindered by their underactuation and strong pose–position coupling, leading to challenges in achieving precise trajectory tracking, especially under high-speed maneuvers. Method: This paper proposes a nonlinear model predictive control (NMPC) framework leveraging dual quaternions to uniformly represent pose–position errors directly on the dual quaternion manifold, thereby avoiding Euler-angle singularities and numerical instabilities during aggressive maneuvers. By integrating differential flatness analysis with real-time optimization, the approach enables singularity-free, compact coupled dynamical modeling and high-fidelity trajectory tracking. Results: Experimental validation demonstrates stable tracking of extreme trajectories—up to 13.66 m/s and 4.2g—in confined spaces. Compared to conventional methods, position and attitude tracking errors are reduced by 56.11% and 56.77%, respectively, significantly enhancing control accuracy and robustness.

Technology Category

• Intelligent Robots: State Estimation
• Planning, Routing, and Scheduling: Replanning and Plan Repair
• Humans and AI: Human-Aware Planning and Behavior Prediction

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Search and Retrieval-Augmented AI: Agentic search
• User Modeling, Personalization and Recommendation: Attacks and countermeasures in recommendation systems

Abstract

MAVs have great potential to assist humans in complex tasks, with applications ranging from logistics to emergency response. Their agility makes them ideal for operations in complex and dynamic environments. However, achieving precise control in agile flights remains a significant challenge, particularly due to the underactuated nature of quadrotors and the strong coupling between their translational and rotational dynamics. In this work, we propose a novel NMPC framework based on dual-quaternions (DQ-NMPC) for quadrotor flight. By representing both quadrotor dynamics and the pose error directly on the dual-quaternion manifold, our approach enables a compact and globally non-singular formulation that captures the quadrotor coupled dynamics. We validate our approach through simulations and real-world experiments, demonstrating better numerical conditioning and significantly improved tracking performance, with reductions in position and orientation errors of up to 56.11% and 56.77%, compared to a conventional baseline NMPC method. Furthermore, our controller successfully handles aggressive trajectories, reaching maximum speeds up to 13.66 m/s and accelerations reaching 4.2 g within confined space conditions of dimensions 11m x 4.5m x 3.65m under which the baseline controller fails.

Problem

• Achieving precise control in agile quadrotor flights
• Addressing underactuated nature and coupled dynamics of quadrotors
• Improving tracking performance for aggressive trajectory maneuvers

Innovation

• Uses dual-quaternion NMPC for quadrotor flight control
• Represents dynamics on dual-quaternion manifold for compact formulation
• Enables globally non-singular formulation of coupled dynamics