References
- Iocchi L, Holz D, Ruiz-Del-Solar J, et al. RoboCup@Home: analysis and results of evolving competitions for domestic and service robots. Artif Intell. 2015;229:258–281.
- Inamura T, Mizuchi Y. SIGVerse: a cloud-based VR platformfor research on social and embodied human-robot interaction. 2020. arXiv:2005.00825v1.
- Okada H, Inamura T, Wada K. What competitions were conducted in the service categories of the world robot summit? Adv Robot. 2019;33(17):900–910.
- Mizuchi Y, Inamura T. Cloud-based multimodal human-robot interaction simulator utilizing ROS and unity frameworks. In: IEEE/SICE International Symposium on System Integration, Taipei, Taiwan; 2017. p. 948–955.
- Inamura T, Mizuchi Y. Robot competition to evaluate guidance skill for general users in VR environment. In: ACM/IEEE International Conference on Human-Robot Interaction, Daegu, Korea; 2019. p. 552–553.
- Mizuchi Y, Inamura T. Optimization of criterion for objective evaluation of HRI performance that approximates subjective evaluation: a case study in robot competition. Adv Robot. 2020;34(3-4):142–156.
- Orkin J, Roy D. The restaurant game: learning social behavior and language from thousands of players online. J Game Dev. 2007;3(1):39–60.
- Breazeal C, DePalma N, Orkin J, et al. Crowdsourcing human-robot interaction: new methods and system evaluation in a public environment. J Hum Rob Interact. 2013;2(1):82–111.
- de Vries H, Shuster K, Batra D, et al. Talk the walk: navigating New York city through grounded dialogue. Preprint, 2018. arXiv:180703367.
- Striegnitz K, Denis A, Gargett A, et al. Report on the second second challenge on generating instructions in virtual environments (GIVE-2.5). In: Proceedings of European Workshop on Natural Language Generation, Nancy, France; 2011. p. 270–279.
- Das A, Datta S, Gkioxari G, et al. Embodied question answering. In: 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, Salt Lake City, USA; 2018. p. 1–10.