Wearable gesture control of agile micro quadrotors

Abstract

Quadrotor unmanned aerial vehicles (UAVs) have seen a surge of use in various applications due to its structural simplicity and high maneuverability. However, conventional control methods using joysticks prohibit novices from getting used to maneuvering quadrotors in short time. In this paper, we suggest the use of a wearable device, such as a smart watch, as a new remote-controller for a quadrotor. The user's command is recognized as gestures using the 9-DoF inertial measurement unit (IMU) of a wearable device through a recurrent neural network (RNN) with long short-term memory (LSTM) cells. Our implementation also makes it possible to align the heading of a quadrotor with the heading of the user. Our implementation allows nine different gestures and the trained RNN is used for real-time gesture recognition for controlling a micro quadrotor. The proposed system exploits available sensors in a wearable device and a quadrotor as much as possible to make the gesture-based control intuitive. We have experimentally validated the performance of the proposed system by using a Samsung Gear S smart watch and a Crazyflie Nano Quadcopter.