Humotion

Schulz, S.; Lier, Florian; Kipp, Andreas; Wachsmuth, Sven

doi:10.1145/2974804.2974827

Cited by 4 publications

(1 citation statement)

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“…This type of actions also allows RISE to receive feedback from the robot about action processing states. Based on the HLRC ( Schulz et al, 2016 ) server message structures, these messages are received by a Robot Wrapper and transformed into robot commands through Robot-APIs . RISE supports two additional ROS interfaces to obtain information about the internal processes within the system.…”

Section: Risementioning

confidence: 99%

RISE: an open-source architecture for interdisciplinary and reproducible human–robot interaction research

Groß,

Schütze,

Brandt

et al. 2023

Front. Robot. AI

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In this article, we present RISE—a Robotics Integration and Scenario-Management Extensible-Architecture—for designing human–robot dialogs and conducting Human–Robot Interaction (HRI) studies. In current HRI research, interdisciplinarity in the creation and implementation of interaction studies is becoming increasingly important. In addition, there is a lack of reproducibility of the research results. With the presented open-source architecture, we aim to address these two topics. Therefore, we discuss the advantages and disadvantages of various existing tools from different sub-fields within robotics. Requirements for an architecture can be derived from this overview of the literature, which 1) supports interdisciplinary research, 2) allows reproducibility of the research, and 3) is accessible to other researchers in the field of HRI. With our architecture, we tackle these requirements by providing a Graphical User Interface which explains the robot behavior and allows introspection into the current state of the dialog. Additionally, it offers controlling possibilities to easily conduct Wizard of Oz studies. To achieve transparency, the dialog is modeled explicitly, and the robot behavior can be configured. Furthermore, the modular architecture offers an interface for external features and sensors and is expandable to new robots and modalities.

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Section: Risementioning

confidence: 99%