SwarMan: Anthropomorphic Swarm of Drones Avatar with Body Tracking and Deep Learning-Based Gesture Recognition
Ahmed Baza, Ayush Gupta, Ekaterina Dorzhieva, Aleksey Fedoseev,, Dzmitry Tsetserukou

TL;DR
This paper introduces SwarMan, an anthropomorphic drone swarm avatar system enabling remote emotional communication through gesture recognition and emotion illumination, offering a lightweight, flexible alternative to traditional telepresence robots.
Contribution
The paper presents a novel drone swarm avatar system with gesture-based control and high-accuracy emotion recognition, enhancing remote affective communication capabilities.
Findings
Emotion recognition accuracy of 97%
High user consistency in emotion perception
Low physical demand and high user satisfaction
Abstract
Anthropomorphic robot avatars present a conceptually novel approach to remote affective communication, allowing people across the world a wider specter of emotional and social exchanges over traditional 2D and 3D image data. However, there are several limitations of current telepresence robots, such as the high weight, complexity of the system that prevents its fast deployment, and the limited workspace of the avatars mounted on either static or wheeled mobile platforms. In this paper, we present a novel concept of telecommunication through a robot avatar based on an anthropomorphic swarm of drones; SwarMan. The developed system consists of nine nanocopters controlled remotely by the operator through a gesture recognition interface. SwarMan allows operators to communicate by directly following their motions and by recognizing one of the prerecorded emotional patterns, thus rendering…
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Taxonomy
TopicsSocial Robot Interaction and HRI · UAV Applications and Optimization · Emotion and Mood Recognition
