News Release

Best of both worlds: Innovative positioning system enhances versatility and accuracy of drone-viewpoint mixed reality applications

Peer-Reviewed Publication

Osaka University

Fig. 1

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Overview of the proposed method. While previous methods operate drones according to predefined flight routes, the proposed method integrates VPS and natural feature-based tracking to estimate the drone's position, thereby matching real-world and virtual-world motion.

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Credit: 🄫2023 Airi Kinoshita et al., Drone Systems and Applications

Osaka, Japan – A research group at Osaka University has developed an innovative positioning system, correctly aligning the coordinates of the real and virtual worlds without the need to define routes in advance. This is achieved by integrating two vision-based self-location estimation methods: visual positioning systems (VPS) and natural feature-based tracking. This development will lead to the realization of versatile drone-based mixed reality (MR) using drones available on the market. Drone-based MR is expected to see use in a variety of applications in the future, such as urban landscape simulation and support for maintenance and inspection work, contributing to further development of drone applications, especially in the fields of architecture, engineering, and construction (AEC).

In recent years, there has been a growing interest in the integration of drones across diverse sectors, particularly within AEC. The use of drones in AEC has expanded due to their superior features in terms of time, accuracy, safety, and cost. The amalgamation of drones with MR stands out as a promising avenue as it is not restricted by the user's range of action and is effective when performing landscape simulations for large-scale spaces such as cities and buildings. Previous studies proposed methods to integrate MR and commercial drones using versatile technologies such as screen sharing and streaming delivery; however, these methods required predefined drone flight routes to match the movements of the real and virtual world, thus reducing the versatility of the application and limiting use cases of MR.

While this research does not implement a drone-based MR application for actual use, the proposed alignment system is highly versatile and has the potential for various additional functionalities in the future. This brings us one step closer to realizing drone-centric MR applications that can be utilized throughout the entire lifecycle of architectural projects, from the initial stages of design and planning to later stages such as maintenance and inspection.

First author Airi Kinoshita mentions, “The integration of drones and MR has the potential to solve various social issues, such as those in urban planning and infrastructure development and maintenance, disaster response and humanitarian aid, cultural protection and tourism, and environmental conservation by freeing MR users from the constraints of experiencing only their immediate vicinity, enabling MR expression from a freer perspective.”

 

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The article, “Drone-Based Mixed Reality: Enhancing Visualization for Large-Scale Outdoor Simulations with Dynamic Viewpoint Adaptation Using Vision-Based Pose Estimation Methods,” was published in Drone Systems and Applications at DOI: https://doi.org/10.1139/dsa-2023-0135

About Osaka University
Osaka University was founded in 1931 as one of the seven imperial universities of Japan and is now one of Japan's leading comprehensive universities with a broad disciplinary spectrum. This strength is coupled with a singular drive for innovation that extends throughout the scientific process, from fundamental research to the creation of applied technology with positive economic impacts. Its commitment to innovation has been recognized in Japan and around the world. Now, Osaka University is leveraging its role as a Designated National University Corporation selected by the Ministry of Education, Culture, Sports, Science and Technology to contribute to innovation for human welfare, sustainable development of society, and social transformation.
Website: https://resou.osaka-u.ac.jp/en


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