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IROS 2020

A Framework for Human-Robot Interaction User Studies

Conference Paper Accepted Paper Artificial Intelligence ยท Robotics

Abstract

Human-Robot Interaction (HRI) user studies are challenging to evaluate and compare due to a lack of standardization and the infrastructure required to implement each study. The lack of experimental infrastructure also makes it difficult to systematically evaluate the impact of individual components (e. g. , the quality of perception software) on overall system performance. This work proposes a framework to ease the implementation and reproducibility of human-robot interaction user studies. The framework utilizes ROS middleware and is implemented with four modules: perception, decision, action, and metrics. The perception module aggregates sensor data to be used by the decision and action modules. The decision module is the task-level executive and can be designed by the HRI researcher for their specific task. The action module takes subtask requests from the decision module and breaks them down into motion primitives for execution on the robot. The metrics module tracks and generates quantitative metrics for the study. The framework is implemented with modular interfaces to allow for alternate implementations within each module and can be generalized for a variety of tasks and human/robot roles. The framework is illustrated through an example scenario involving a human and a Franka Emika Panda arm collaboratively assembling a toolbox together.

Authors

Keywords

  • Measurement
  • Tracking
  • System performance
  • Human-robot interaction
  • Standardization
  • Robot sensing systems
  • Task analysis
  • User Study
  • Standardised
  • Quantitative Metrics
  • Robot Operating System
  • Metrics In Studies
  • Perception Module
  • Motion Primitives
  • Interactive
  • Human Activities
  • Human Participants
  • Tracking System
  • Design Stage
  • Path Planning
  • Full Study
  • Team Performance
  • Stopping Rule
  • Application Context
  • Common Metrics
  • Collaborative Tasks
  • Set Of Metrics
  • Human-robot Collaboration
  • Objective Metrics
  • Object Pose
  • Query Point
  • Task Planning
  • Interaction Scenarios
  • Software Framework
  • Architectural Framework

Context

Venue
IEEE/RSJ International Conference on Intelligent Robots and Systems
Archive span
1988-2025
Indexed papers
26578
Paper id
695403266301401706
v2026.09.13