Header

UZH-Logo

Maintenance Infos

Robotic interfaces for cognitive psychology and embodiment research: A research roadmap


Beckerle, Philipp; Castellini, Claudio; Lenggenhager, Bigna (2018). Robotic interfaces for cognitive psychology and embodiment research: A research roadmap. Wiley Interdisciplinary Reviews: Cognitive Science:e1486.

Abstract

Advanced human-machine interfaces render robotic devices applicable to study and enhance human cognition. This turns robots into formidable neuroscientific tools to study processes such as the adaptation between a human operator and the operated robotic device and how this adaptation modulates human embodiment and embodied cognition. We analyze bidirectional human-machine interface (bHMI) technologies for transparent information transfer between a human and a robot via efferent and afferent channels. Even if such interfaces have a tremendous positive impact on feedback loops and embodiment, advanced bHMIs face immense technological challenges. We critically discuss existing technical approaches, mainly focusing on haptics, and suggest extensions thereof, which include other aspects of touch. Moreover, we point out other potential constraints such as limited functionality, semi-autonomy, intent-detection, and feedback methods. From this, we develop a research roadmap to guide understanding and development of bidirectional human-machine interfaces that enable robotic experiments to empirically study the human mind and embodiment. We conclude the integration of dexterous control and multisensory feedback to be a promising roadmap towards future robotic interfaces, especially regarding applications in the cognitive sciences. This article is categorized under: Computer Science > Robotics Psychology > Motor Skill and Performance Neuroscience > Plasticity.

Abstract

Advanced human-machine interfaces render robotic devices applicable to study and enhance human cognition. This turns robots into formidable neuroscientific tools to study processes such as the adaptation between a human operator and the operated robotic device and how this adaptation modulates human embodiment and embodied cognition. We analyze bidirectional human-machine interface (bHMI) technologies for transparent information transfer between a human and a robot via efferent and afferent channels. Even if such interfaces have a tremendous positive impact on feedback loops and embodiment, advanced bHMIs face immense technological challenges. We critically discuss existing technical approaches, mainly focusing on haptics, and suggest extensions thereof, which include other aspects of touch. Moreover, we point out other potential constraints such as limited functionality, semi-autonomy, intent-detection, and feedback methods. From this, we develop a research roadmap to guide understanding and development of bidirectional human-machine interfaces that enable robotic experiments to empirically study the human mind and embodiment. We conclude the integration of dexterous control and multisensory feedback to be a promising roadmap towards future robotic interfaces, especially regarding applications in the cognitive sciences. This article is categorized under: Computer Science > Robotics Psychology > Motor Skill and Performance Neuroscience > Plasticity.

Statistics

Citations

Dimensions.ai Metrics
2 citations in Web of Science®
2 citations in Scopus®
Google Scholar™

Altmetrics

Additional indexing

Item Type:Journal Article, not_refereed, original work
Communities & Collections:06 Faculty of Arts > Institute of Psychology
Dewey Decimal Classification:150 Psychology
Language:English
Date:28 November 2018
Deposited On:22 Jan 2019 10:11
Last Modified:17 Sep 2019 19:55
Publisher:Wiley-Blackwell Publishing, Inc.
ISSN:1939-5078
OA Status:Closed
Publisher DOI:https://doi.org/10.1002/wcs.1486
PubMed ID:30485732
Project Information:
  • : FunderSNSF
  • : Grant IDPP00P1_170511
  • : Project TitlePlasticity of the bodily self in a life span approach
  • : FunderGerman Research Foundation
  • : Grant ID
  • : Project Title

Download

Full text not available from this repository.
View at publisher

Get full-text in a library