Abstract
Estimating the real-time pose of a free flight aircraft in a complex wind tunnel environment is extremely difficult. Due to the high dynamic testing environment, complicated illumination condition, and the unpredictable motion of target, most general pose estimating methods will fail. In this paper, we introduce a cross-field of view (FOV) real-time pose estimation system, which provides high precision pose estimation of the free flight aircraft in the wind tunnel environment. Multiview live RGB-D streams are used in the system as input to ensure the measurement area can be fully covered. First, a multimodal initialization method is developed to measure the spatial relationship between the RGB-D camera and the aircraft. Based on all the input multimodal information, a so-called cross-FOV model is proposed to recognize the dominating sensor and accurately extract the foreground region in an automatic manner. Second, we develop an RGB-D-based pose estimation method for a single target, by which the 3D sparse points and the pose of the target can be simultaneously obtained in real time. Many experiments have been conducted, and an RGB-D image simulation based on 3D modeling is implemented to verify the effectiveness of our algorithm. Both the real scene’s and simulation scene’s experimental results demonstrate the effectiveness of our method.
Highlights
Aircraft attitude estimation plays a crucial role in aircraft control systems of the wind tunnel
A multimodal initialization method is developed to measure the spatial relationship between the RGB-D camera and the aircraft
We proposed a cross-field of view (FOV) RGB-D pose estimation system that processes each new frame in real time
Summary
Aircraft attitude estimation plays a crucial role in aircraft control systems of the wind tunnel. The main reason is that the wind tunnel is a high dynamic testing environment and there often exist a complex illumination condition and unpredictable motion of the target. These will heavily decrease the measurement accuracy of the estimation system. Template matching methods [5] are usually applied to weakly textured scenes Such methods need to reconstruct 3D objects and match real scenes with 3D models to find the best pose. According to the experiment results, the pose estimation system with the cross-FOV model can get accurate measurement results in a wind tunnel. We will apply our system on the low-speed wind tunnel of China Aerodynamics Research and Development Centre (CARDC)
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