HOTSPOT: An ad hoc teamwork platform for mixed human-robot teams.

Autor: Ribeiro JG; INESC-ID, Instituto Superior Técnico, Universidade de Lisboa, Lisboa, Portugal., Henriques LM; Departamento de Informática, Pontifícia Universidade Católica do Rio de Janeiro, Rio de Janeiro, Brasil., Colcher S; Departamento de Informática, Pontifícia Universidade Católica do Rio de Janeiro, Rio de Janeiro, Brasil., Duarte JC; Seção de Ensino de Engenharia de Computação, Instituto Militar de Engenharia, Rio de Janeiro, Brasil., Melo FS; INESC-ID, Instituto Superior Técnico, Universidade de Lisboa, Lisboa, Portugal., Milidiú RL; Departamento de Informática, Pontifícia Universidade Católica do Rio de Janeiro, Rio de Janeiro, Brasil., Sardinha A; INESC-ID, Instituto Superior Técnico, Universidade de Lisboa, Lisboa, Portugal.; Departamento de Informática, Pontifícia Universidade Católica do Rio de Janeiro, Rio de Janeiro, Brasil.
Jazyk: angličtina
Zdroj: PloS one [PLoS One] 2024 Jun 28; Vol. 19 (6), pp. e0305705. Date of Electronic Publication: 2024 Jun 28 (Print Publication: 2024).
DOI: 10.1371/journal.pone.0305705
Abstrakt: Ad hoc teamwork is a research topic in multi-agent systems whereby an agent (the "ad hoc agent") must successfully collaborate with a set of unknown agents (the "teammates") without any prior coordination or communication protocol. However, research in ad hoc teamwork is predominantly focused on agent-only teams, but not on agent-human teams, which we believe is an exciting research avenue and has enormous application potential in human-robot teams. This paper will tap into this potential by proposing HOTSPOT, the first framework for ad hoc teamwork in human-robot teams. Our framework comprises two main modules, addressing the two key challenges in the interaction between a robot acting as the ad hoc agent and human teammates. First, a decision-theoretic module that is responsible for all task-related decision-making (task identification, teammate identification, and planning). Second, a communication module that uses natural language processing to parse all communication between the robot and the human. To evaluate our framework, we use a task where a mobile robot and a human cooperatively collect objects in an open space, illustrating the main features of our framework in a real-world task.
Competing Interests: The authors have declared that no competing interests exist.
(Copyright: © 2024 Ribeiro et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)
Databáze: MEDLINE
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