ICUAS'22 Paper Abstract

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Paper ThA2.1

Chaudhary, Akash (Czech Technical University in Prague), Nascimento, Tiago (Universidade Federal da Paraiba), Saska, Martin (Czech Technical University in Prague FEE)

Controlling a Swarm of Unmanned Aerial Vehicles Using Full-Body K-Nearest Neighbor Based Action Classifier

Scheduled for presentation during the Regular Session "Perception and Cognition" (ThA2), Thursday, June 23, 2022, 10:30−10:50, Bokar

2022 International Conference on Unmanned Aircraft Systems (ICUAS), June 21-24, 2022, Dubrovnik, Croatia

This information is tentative and subject to change. Compiled on March 29, 2024

Keywords Perception and Cognition, Swarms, Micro- and Mini- UAS

Abstract

The intuitive control of robot swarms becomes crucial when humans are working in close proximity with the swarm in unknown environments. In such operations, it is necessary to maintain the autonomy of the swarm while giving the human operator enough means to influence the decision-making process of the robots. This paper presents a human-swarm interaction approach using full-body action recognition to control an autonomous flock of unmanned aerial vehicles. We estimate the full-body pose of the human operator and use a k-nearest neighbor algorithm to classify the action made by the humans. Finally, the swarm uses the identified action to decide its goal direction. We demonstrate the practicality of our approach with a multi-stage experimental setup to evaluate the prediction accuracy and robustness of the system.

 

 

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