Abstract / Description of output
We present the publicly-available Robot Open Street Map Instructions (ROSMI) corpus: a rich multimodal dataset of map and natural language instruction pairs that was collected via crowdsourcing. The goal of this corpus is to aid in the advancement of state-of-the-art visual-dialogue tasks, including reference resolution and robot-instruction understanding. The domain described here concerns robots and autonomous systems being used for inspection and emergency response. The ROSMI corpus is unique in that it captures interaction grounded in map-based visual stimuli that is both human-readable but also contains rich metadata that is needed to plan and deploy robots and autonomous systems, thus facilitating human-robot teaming.
Original language | English |
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Title of host publication | ICMI '20: Proceedings of the 2020 International Conference on Multimodal Interaction |
Place of Publication | United States |
Publisher | ACM Association for Computing Machinery |
Pages | 680-684 |
Number of pages | 5 |
ISBN (Electronic) | 9781450375818 |
DOIs | |
Publication status | Published - 21 Oct 2020 |
Event | ICMI '20: International Conference on Multimodal Interaction. Virtual Event - , Netherlands Duration: 25 Oct 2020 → 29 Oct 2020 |
Conference
Conference | ICMI '20: International Conference on Multimodal Interaction. Virtual Event |
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Abbreviated title | 22nd ICMI 2020 |
Country/Territory | Netherlands |
Period | 25/10/20 → 29/10/20 |
Keywords / Materials (for Non-textual outputs)
- crowdsourcing
- data collection
- dialogue system
- human-robot interaction
- multimodal