Control of a Quadrotor Helicopter Using Dual Camera Visual Feedback

TLDR

The paper proposes a vision‑based stabilization and output‑tracking control method for a model helicopter. The method uses a novel two‑camera configuration—one on the helicopter and one on the ground that view each other—to estimate the full six‑degrees‑of‑freedom pose, and implements two control strategies: mode‑based feedback‑linearizing and backstepping‑like laws. Simulations and flight experiments show that the pose estimation algorithm is less sensitive to feature‑detection errors, and that both control strategies successfully stabilize and track the helicopter.

Abstract

In this paper we propose a vision-based stabilization and output tracking control method for a model helicopter. A novel two-camera method is introduced for estimating the full six-degrees-of-freedom pose of the helicopter. One of these cameras is located on-board the helicopter, and the other camera is located on the ground. Unlike previous work, these two cameras are set to see each other. The pose estimation algorithm is compared in simulation to other methods and is shown to be less sensitive to errors on feature detection. In order to build an autonomous helicopter, two methods of control are studied: one using a series of mode-based, feedback linearizing controllers and the other using a backstepping-like control law. Various simulations demonstrate the implementation of these controllers. Finally, we present flight experiments where the proposed pose estimation algorithm and non-linear control techniques have been implemented on a remote-controlled helicopter.