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2020, 2(6): 518-533

Published Date:2020-12-20 DOI: 10.1016/j.vrih.2020.05.006

A multichannel human-swarm robot interaction system in augmented reality


A large number of robots have put forward the new requirements for human-robot interaction. One of the problems in human-swarm robot interaction is how to naturally achieve an efficient and accurate interaction between humans and swarm robot systems. To address this, this paper proposes a new type of human-swarm natural interaction system.
Through the cooperation between three-dimensional (3D) gesture interaction channel and natural language instruction channel, a natural and efficient interaction between a human and swarm robots is achieved.
First, A 3D lasso technology realizes a batch-picking interaction of swarm robots through oriented bounding boxes. Second, control instruction labels for swarm-oriented robots are defined. The instruction label is integrated with the 3D gesture and natural language through instruction label filling. Finally, the understanding of natural language instructions is realized through a text classifier based on the maximum entropy model. A head-mounted augmented reality display device is used as a visual feedback channel.
The experiments on selecting robots verify the feasibility and availability of the system.


Human-swarm interaction ; Augmented reality ; Multichannel integration

Cite this article

Mingxuan CHEN, Ping ZHANG, Zebo WU, Xiaodan CHEN. A multichannel human-swarm robot interaction system in augmented reality. Virtual Reality & Intelligent Hardware, 2020, 2(6): 518-533 DOI:10.1016/j.vrih.2020.05.006


1. Alfeo A L, Cimino M G C A, de Francesco N, Lazzeri A, Lega M, Vaglini G. Swarm coordination of mini-UAVs for target search using imperfect sensors. Intelligent Decision Technologies, 2018, 12(2): 149–162 DOI:10.3233/idt-170317

2. Li K, Ni W, Wang X, Liu R P, Kanhere S S, Jha S. Energy-efficient cooperative relaying for unmanned aerial vehicles. IEEE Transactions on Mobile Computing, 2016, 15(6): 1377–1386 DOI:10.1109/tmc.2015.2467381

3. Zhang Q, Gong Z K, Yang Z Q, Chen Z Q. Distributed convex optimization for flocking of nonlinear multi-agent systems. International Journal of Control, Automation and Systems, 2019, 17(5): 1177–1183 DOI:10.1007/s12555-018-0191-x

4. Krause J, Ruxton G D, Krause S. Swarm intelligence in animals and humans. Trends in Ecology & Evolution, 2010, 25(1): 28–34 DOI:10.1016/j.tree.2009.06.016

5. Vassev E, Hinchey M, Nixon P. A formal approach to self-configurable swarm-based space-exploration systems. 2010 NASA/ESA Conference on Adaptive Hardware and Systems. Anaheim, CA, USA, IEEE, 2010, 83–90 DOI:10.1109/ahs.2010.5546276

6. Kolling A, Walker P, Chakraborty N, Sycara K, Lewis M. Human interaction with robot swarms: a survey. IEEE Transactions on Human-Machine Systems, 2016, 46(1): 9–26 DOI:10.1109/thms.2015.2480801

7. Krishnamurthy P, Khorrami F. A distributed monitoring approach for human interaction with multi-robot systems. In: Proceedings of the Companion of the 2017 ACM/IEEE International Conference on Human-Robot Interaction. Vienna Austria, New York, NY, USA, ACM, 2017 DOI:10.1145/3029798.3038327

8. Savla K, Frazzoli E. A dynamical queue approach to intelligent task management for human operators. Proceedings of the IEEE, 2012, 100(3): 672–686 DOI:10.1109/jproc.2011.2173264

9. Setter T, Fouraker A, Kawashima H, Egerstedt M. Haptic interactions with multi-robot swarms using manipulability. Journal of Human-Robot Interaction, 2015, 4(1): 60–74 DOI:10.5898/jhri.4.1.setter

10. Franchi A, Secchi C, Ryll M, Bulthoff H, Giordano P. Shared control: balancing autonomy and human assistance with a group of quadrotor UAVs. IEEE Robotics & Automation Magazine, 2012, 19(3): 57–68 DOI:10.1109/mra.2012.2205625

11. Wang Z J, Schwager M. Kinematic multi-robot manipulation with no communication using force feedback. In: 2016 IEEE International Conference on Robotics and Automation (ICRA). Stockholm, Sweden, IEEE, 2016, 427–432 DOI:10.1109/icra.2016.7487163

12. Gromov B, Gambardella L M, di Caro G A. Wearable multi-modal interface for human multi-robot interaction. In: 2016 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR). Lausanne, Switzerland, IEEE, 2016, 240–245 DOI:10.1109/ssrr.2016.7784305

13. Erat O, Isop W A, Kalkofen D, Schmalstieg D. Drone-augmented human vision: exocentric control for drones exploring hidden areas. IEEE Transactions on Visualization and Computer Graphics, 2018, 24(4): 1437–1446 DOI:10.1109/tvcg.2018.2794058

14. Tsykunov E, Agishev R, Ibrahimov R, Labazanova L, Tleugazy A, Tsetserukou D. SwarmTouch: guiding a swarm of micro-quadrotors with impedance control using a wearable tactile interface. IEEE Transactions on Haptics, 2019, 12(3): 363–374 DOI:10.1109/toh.2019.2927338

15. Zhang Y H, Du Y, Pan F, Wei Y. Intelligent vehicle path tracking algorithm based on cubic B-spline curve fitting. Journal of Computer Applications, 2018, 38(6): 1562–1567(in Chinese)

16. Zhai Y, Xu W Y, Zhang Q. Judgment of topological relation between point and polygon or polyhedron. Computer Engineering and Design, 2015, 36(4): 972–976(in Chinese) DOI:10.16208/j.issn1000-7024.2015.04.026

17. Du G L, Chen M X, Liu C B, Zhang B, Zhang P. Online robot teaching with natural human–robot interaction. IEEE Transactions on Industrial Electronics, 2018, 65(12): 9571–9581 DOI:10.1109/tie.2018.2823667


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