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Co-adaptive Human–Robot Cooperation: Summary and Challenges

Sofie Ahlberg

Department of Intelligent Systems, KTH Royal Institute of Technology, Stockholm, Sweden

E-mail Address: sofa@kth.se

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Agnes Axelsson

Department of Intelligent Systems, KTH Royal Institute of Technology, Stockholm, Sweden

E-mail Address: agnaxe@kth.se

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Pian Yu

Department of Intelligent Systems, KTH Royal Institute of Technology, Stockholm, Sweden

E-mail Address: piany@kth.se

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Wenceslao Shaw Cortez

https://orcid.org/0000-0002-1809-5656

Department of Intelligent Systems, KTH Royal Institute of Technology, Stockholm, Sweden

E-mail Address: wencsc@kth.se

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Yuan Gao

Department of Information Technology, Uppsala University, Uppsala, Sweden

Center for Intelligent Robots, Shenzhen Institute of Artificial Intelligence and Robotics for Society, Shenzhen, P. R. China

E-mail Address: gaoyuankidult@gmail.com

Most of the work was done at Uppsala University.

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Ali Ghadirzadeh

Department of Intelligent Systems, KTH Royal Institute of Technology, Stockholm, Sweden

E-mail Address: algh@kth.se

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Ginevra Castellano

Department of Information Technology, Uppsala University, Uppsala, Sweden

E-mail Address: ginevra.castellano@it.uu.se

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Danica Kragic

Department of Intelligent Systems, KTH Royal Institute of Technology, Stockholm, Sweden

E-mail Address: dani@kth.se

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Gabriel Skantze

Department of Intelligent Systems, KTH Royal Institute of Technology, Stockholm, Sweden

E-mail Address: gabriel@speech.kth.se

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, and

Dimos V. Dimarogonas

Department of Intelligent Systems, KTH Royal Institute of Technology, Stockholm, Sweden

E-mail Address: dimos@kth.se

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https://doi.org/10.1142/S230138502250011XCited by:6 (Source: Crossref)

Abstract

The work presented here is a culmination of developments within the Swedish project COIN: Co-adaptive human-robot interactive systems, funded by the Swedish Foundation for Strategic Research (SSF), which addresses a unified framework for co-adaptive methodologies in human–robot co-existence. We investigate co-adaptation in the context of safe planning/control, trust, and multi-modal human–robot interactions, and present novel methods that allow humans and robots to adapt to one another and discuss directions for future work.

This paper was recommended for publication in its revised form by co-editor-in-chief, Ben M. Chen.

Keywords:

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