In this video we demonstrate an intuitive gesture-based interface for manually guiding a drone to land on a precise spot. Using unobtrusive wearable sensors, an operator can quickly and accurately maneuver and land the drone after very little training; a preliminary user study on 5 subjects shows that the system compares favorably with a traditional joystick interface.

The video has been accepted for publication at Human-Robot Interaction (HRI 2018) conference [1], March 5-8, 2018, Chicago, IL, USA.

To detect the events of pointing we used 1-D convolutional neural network (CNN) that receives a stream of acceleration and orientation data from two inertial measurement units (IMUs) placed on user’s arm [2].

#### Design of the user study

Video demonstration of a part of experimental sequence performed in the user study.

The next video shows collated trajectory animations for all the subjects for two interfaces: joystick (blue) and pointing (green). The popping dots over the right target signify the landing of the drone:

The Python code and corresponding dataset (ROS bag-files) can be used to reproduce the results presented in this work.

#### Example of Guiding and Landing

An example of pointing gestures being used for steering and landing a drone:

#### Acknowledgment

This work was partially supported by the Swiss National Science Foundation (SNSF) through the National Centre of Competence in Research (NCCR) Robotics.

#### Publications

1. B. Gromov, L. Gambardella, and A. Giusti, “Video: Landing a Drone with Pointing Gestures,” in HRI ’18 Companion: 2018 ACM/IEEE International Conference on Human-Robot Interaction Companion, March 5–8, 2018, Chicago, IL, USA, 2018.

@inproceedings{gromov2018video,
author = {Gromov, Boris and Gambardella, Luca and Giusti, Alessandro},
title = {Video: Landing a Drone with Pointing Gestures},
booktitle = {HRI~'18 Companion: 2018 ACM/IEEE International Conference on Human-Robot Interaction Companion, March 5--8, 2018, Chicago, IL, USA},
conference = {2018 ACM/IEEE International Conference on Human-Robot Interaction Companion},
doi = {10.1145/3173386.3177530},
isbn = {978-1-4503-5615-2/18/03},
location = {Chicago, IL, USA},
year = {2018},
month = mar,
acmid = {3177530},
publisher = {ACM},
video = {https://youtu.be/jpG8Jsmth2Y},
}

2. D. Broggini, B. Gromov, L. M. Gambardella, and A. Giusti, “Learning to detect pointing gestures from wearable IMUs,” in Proceedings of Thirty-Second AAAI Conference on Artificial Intelligence, February 2-7, 2018, New Orleans, Louisiana, USA, 2018.

@inproceedings{broggini2018learning,
author = {Broggini, Denis and Gromov, Boris and Gambardella, Luca M. and Giusti, Alessandro},
title = {Learning to detect pointing gestures from wearable {IMUs}},
booktitle = {Proceedings of Thirty-Second {AAAI} Conference on Artificial Intelligence, February 2-7, 2018, New Orleans, Louisiana, {USA}},
year = {2018},
month = feb,
publisher = {{AAAI} Press},
url = {https://www.aaai.org/ocs/index.php/AAAI/AAAI18/paper/view/16259/16463},
}