Drone Operation with Human Natural Movement

This study proposes a method for operating drones using natural human movements. The operator simply wears virtual reality (VR) goggles. An image from the drone camera was displayed on the goggles. When the operator changes the direction of his or her face, the drone changes the direction to match that of the operator. When the operator moves their head up or down, the drone rises or falls accordingly. When the operator walks in place, rather than walking, the drone moves forward. This allows the operator to control the drone as if they were walking in the air. Each of these movements was detected by the values of the acceleration and magnetic field sensors of the smartphone mounted on the VR goggles. A machine learning method was adopted to distinguish between walking and non-walking movements. Compared with operation via conventional remote control, it was observed that the remote controller performed better than the proposed approach in the early stages. However, when the participants familiarized themselves with the natural operation, these differences became relatively small. This study combined drones, VR, and machine learning. VR provides drone pilots with a sense of realism and immersion, whereas machine learning enables the use of natural movements.

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Publication Details

Journal
Drones and autonomous vehicles/Drones and Autonomous Vehicles
Published
2025-01-01
DOI
https://doi.org/10.70322/dav.2025.10011
Primary Topic
Robotic Path Planning Algorithms
Type
article
Field-Weighted Citation Impact
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article

Drone Operation with Human Natural Movement

Hironori Hiraishi
Drones and autonomous vehicles/Drones and Autonomous Vehicles
Robotic Path Planning Algorithms
article

Drone Operation with Human Natural Movement

Hironori Hiraishi
article en

Abstract

This study proposes a method for operating drones using natural human movements. The operator simply wears virtual reality (VR) goggles. An image from the drone camera was displayed on the goggles. When the operator changes the direction of his or her face, the drone changes the direction to match that of the operator. When the operator moves their head up or down, the drone rises or falls accordingly. When the operator walks in place, rather than walking, the drone moves forward. This allows the operator to control the drone as if they were walking in the air. Each of these movements was detected by the values of the acceleration and magnetic field sensors of the smartphone mounted on the VR goggles. A machine learning method was adopted to distinguish between walking and non-walking movements. Compared with operation via conventional remote control, it was observed that the remote controller performed better than the proposed approach in the early stages. However, when the participants familiarized themselves with the natural operation, these differences became relatively small. This study combined drones, VR, and machine learning. VR provides drone pilots with a sense of realism and immersion, whereas machine learning enables the use of natural movements.

Drones and autonomous vehicles/Drones and Autonomous VehiclesVol. 2(3)
Ashikaga University (JP)
Zero hunger
Openalex Percentile: Top 92%
Robotic Path Planning Algorithms
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