arXiv 2107.112882021-07-23cs.RO

DronePaint: Swarm Light Painting with DNN-based Gesture Recognition

Skolkovo Institute of Science and Technology（斯科尔科沃科学技术研究院）

Valerii Serpiva, Ekaterina Karmanova, Aleksey Fedoseev, Stepan Perminov, Dzmitry Tsetserukou

备注：: ACM SIGGRAPH 21. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. arXiv admin note: substantial text overlap with arXiv:2106.14698
DOI：: 10.1145/3450550.3465349

英文摘要：

We propose a novel human-swarm interaction system, allowing the user to directly control a swarm of drones in a complex environment through trajectory drawing with a hand gesture interface based on the DNN-based gesture recognition. The developed CV-based system allows the user to control the swarm behavior without additional devices through human gestures and motions in real-time, providing convenient tools to change the swarm's shape and formation. The two types of interaction were proposed and implemented to adjust the swarm hierarchy: trajectory drawing and free-form trajectory generation control. The experimental results revealed a high accuracy of the gesture recognition system (99.75%), allowing the user to achieve relatively high precision of the trajectory drawing (mean error of 5.6 cm in comparison to 3.1 cm by mouse drawing) over the three evaluated trajectory patterns. The proposed system can be potentially applied in complex environment exploration, spray painting using drones, and interactive drone shows, allowing users to create their own art objects by drone swarms.

机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。