TeAMH-Robot · Temporal Adaptation and anticipation Mechanisms in Human-Robot interaction
Horizon 2020 — Marie Skłodowska-Curie Actions
- Duration
- 2021-08-01 → 2023-08-31
- EU contribution
- €171,473
- Participants
- 2
- Scheme
- MSCA-IF
Lines connect the coordinator with its partners.
Results in brief
Temporal Adaptation and anticipation Mechanisms in Human-Robot interaction
The advent of robots will change the role that artificial agents play in our lives, as the interaction with them will not be limited to specialized and well-structured work environments. When interacting with artificial agents, humans often encounter the Out of The Loop phenomenon (OOTL), which is a difficulty to predict and prevent failures, probably due to a lack of transparency in artificial agents' actions. The overarching aim of TeAMH-Robot was to develop a model of Human-Robot Interaction (HRI) that will prevent the OOTL phenomenon when interacting with robots. To this end, TeAMH-Robot used a novel approach to develop an efficient HRI that combines cognitive neuroscience methods with real-time interactive tasks with a humanoid robot. Firstly, TeAMH-Robot tried to understand how temporal adaptation and anticipation mechanisms allow humans to “stay in the loop” when mistakes occur. Then, TeAMH-Robot used this knowledge to implement a human-inspired computational model on a humanoid robot that ensures real-time coordination. Finally, TeAMH-Robot tested the efficiency of human-inspired behaviour in reducing the impact of the OOTL phenomenon. TeAMH-Robot has significantly extended the state of the art both in the field of cognitive neuroscience and robotics. In the former case, TeAMH-Robot highlighted that humans successfully stay in the loop in coordination tasks characterized by errors by adopting a priori top-down control and relying mostly on reactive temporal error correction mechanisms instead of anticipation. In the latter case, TeAMH-Robot showed that implementing human-inspired mutual adaptation on humanoid robots reduces the probability of the OOTL phenomena and increases shared agency promoting effective HRI. Finally,TeAMH-Robot increased the independence of the ER and enriched her expertise in transferable skills, such as grant writing, teaching, dissemination, and outreach.
Data: CORDIS, © European Union
Project objective
In the near future, the advent of robots will change the role that artificial agents play in our life, as the interaction with them will not be limited to specialized and well-structured work environments. When interacting with artificial agents, humans often occur into the Out of The Loop phenomenon (OOTL), that is a difficulty to predict and prevent failures, probably due to a lack of transparency in artificial agents actions. The overarching aim of TeAMH-Robot is to develop a model of Human-Robot Interaction (HRI) that will prevent the OOTL phenomenon when interacting with robots. To this end, TeAMH-Robot will use a novel approach to develop efficient HRI that combines cognitive neuroscience methods with real-time interactive tasks with a humanoid robot. Firstly, TeAMH-Robot will aim to understand how temporal adaptation and anticipation mechanisms allow humans to “stay in the loop” when mistakes occur. Then, TeAMH-Robot will use this knowledge to develop a human-inspired module for humanoid robots that ensure real-time coordination. Finally, TeAMH-Robot will test the efficiency of human-inspired behaviour in reducing the impact of the OOTL phenomenon. The outgoing phase will be hosted by the Western Sydney University (Australia), where the ER will (i) identify and (ii) model temporal adaptation and anticipation mechanisms that allow humans to predict, prevent and recover mistakes. The return phase will be hosted by the Italian Institute of Technology (Italy), where the ER will (iii) develop a module for humanoid robots that ensure real-time coordination and (iv) test its efficiency in reducing the OOTL by means of the acquired neurocognitive methods. TeAMH-Robot will increase ER’s expertise on social cognitive mechanisms and allow her to start her independency. Moreover, the fellowship will enable the ER to build an international and interdisciplinary network. The results of TeAMH-Robot have the potential to promote the exploitation of robots in everyday life.
Original text from CORDIS.
Participants
Links
Data: CORDIS, © European Union