Wall Inspector: Quadrotor Control in Wall-proximity Through Model Compensation

2025-09-25

AI Summary

Quadrotor UAVs operating near walls—e.g., in urban canyons or indoor environments—suffer trajectory instability and collision risks due to unmodeled wall-induced suction forces arising from vortex effects. Method: This paper proposes a robust control framework integrating physics-informed modeling with model predictive control (MPC). We derive an analytical suction force model dependent on rotor speeds and distance to the wall, embed it into an MPC formulation with explicit suction compensation, and unify nonlinear dynamics constraints and multi-objective control requirements via factor graph optimization. Results: Evaluated on a fully enclosed ducted quadrotor platform, the method achieves X- and Y-axis positioning RMSEs of 2.1 cm and 2.0 cm, respectively—significantly outperforming conventional PID and standard MPC. To our knowledge, this is the first work enabling both modeling and active compensation of wall-induced suction, thereby achieving high-precision trajectory tracking near boundaries and establishing a new paradigm for safe autonomous flight in complex, confined spaces.

Technology Category

• Intelligent Robots: State Estimation
• Search and Optimization: Mixed Discrete/Continuous Search
• Planning, Routing, and Scheduling: Replanning and Plan Repair

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Systems and Infrastructure for Web, Mobile and WoT: Location- and context-aware Web and WoT applications and services
• User Modeling, Personalization and Recommendation: Attacks and countermeasures in recommendation systems

Abstract

The safe operation of quadrotors in near-wall urban or indoor environments (e.g., inspection and search-and-rescue missions) is challenged by unmodeled aerodynamic effects arising from wall-proximity. It generates complex vortices that induce destabilizing suction forces, potentially leading to hazardous vibrations or collisions. This paper presents a comprehensive solution featuring (1) a physics-based suction force model that explicitly characterizes the dependency on both rotor speed and wall distance, and (2) a suction-compensated model predictive control (SC-MPC) framework designed to ensure accurate and stable trajectory tracking during wall-proximity operations. The proposed SC-MPC framework incorporates an enhanced dynamics model that accounts for suction force effects, formulated as a factor graph optimization problem integrating system dynamics constraints, trajectory tracking objectives, control input smoothness requirements, and actuator physical limitations. The suction force model parameters are systematically identified through extensive experimental measurements across varying operational conditions. Experimental validation demonstrates SC-MPC's superior performance, achieving 2.1 cm root mean squared error (RMSE) in X-axis and 2.0 cm RMSE in Y-axis position control - representing 74% and 79% improvements over cascaded proportional-integral-derivative (PID) control, and 60% and 53% improvements over standard MPC respectively. The corresponding mean absolute error (MAE) metrics (1.2 cm X-axis, 1.4 cm Y-axis) similarly outperform both baselines. The evaluation platform employs a ducted quadrotor design that provides collision protection while maintaining aerodynamic efficiency. To facilitate reproducibility and community adoption, we have open-sourced our complete implementation, available at https://anonymous.4open.science/r/SC-MPC-6A61.

Problem

• Modeling wall-proximity aerodynamic effects on quadrotors
• Compensating suction forces for stable near-wall flight
• Improving trajectory tracking accuracy in confined environments

Innovation

• Physics-based suction force model for wall proximity
• Suction-compensated model predictive control framework
• Factor graph optimization integrating dynamics and constraints