DR-IPC: Disturbance-Resilient Integrated Planning and Control for LiDAR-Based Quadrotor Navigation

2026-10-02

AI Summary

This study addresses the limited robustness of LiDAR-equipped quadrotors under complex disturbances caused by the separation of planning and control. To this end, a disturbance-robust integrated planning and control (DR-IPC) navigation framework is proposed. This method fuses path guidance with nonlinear model predictive control (NMPC), eliminating the need for independent trajectory optimization. By unifying dynamics, constraints, and safety corridors, it directly generates angular velocity and thrust commands. Furthermore, an interconnected extended Kalman filter and a nonlinear disturbance observer are synergistically employed to achieve precise state estimation and disturbance compensation. Experimental results demonstrate that the task completion rate increases from 10% to 90%, the altitude root mean square error (RMSE) is reduced to 0.01 m, and the onboard computational frequency reaches 100 Hz.

Abstract

LiDAR-based quadrotor navigation in cluttered environments remains challenging under external disturbances, particularly when obstacle-aware motion generation and disturbance-rejection control are handled in separate layers. This article presents disturbance-resilient integrated planning and control (DR-IPC), which combines lightweight path guidance with nonlinear model predictive control (NMPC) to directly generate angular velocity and thrust. An interconnected extended Kalman filter and nonlinear disturbance observer jointly provide filtered state estimates and reconstructed disturbances for NMPC prediction. The resulting formulation unifies nonlinear quadrotor dynamics, actuator constraints, local motion generation, and penalised safe-flight-corridor residuals without requiring a separate trajectory-optimization stage. Gazebo and MARSIM simulations, together with indoor and outdoor experiments, validate DR-IPC under wind, suspended payloads, narrow passages, ball impacts and reactive avoidance of a dynamic obstacle. In multi-goal navigation with disturbances, DR-IPC increases the number of completed missions from 1/10 to 9/10 in Gazebo and reduces the altitude RMSE from 0.34 to 0.01 m in experiments. The complete system operates onboard at 100 Hz. Supplementary videos are available on the project page https://drpp316.github.io/DR-IPC-Page/, and the source code will be released.

Problem

• Quadrotor Navigation
• External Disturbances
• LiDAR
• Cluttered Environments
• Integrated Planning and Control

Innovation

• Disturbance-Resilient Control
• Nonlinear Model Predictive Control
• Integrated Planning and Control
• Nonlinear Disturbance Observer
• LiDAR Navigation