Online User Assessment for Minimal Intervention During Task-Based Robotic Assistance

Aleksandra Kalinowska, Kathleen Fitzsimons, Julius Dewald, Todd D. Murphey

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Scopus citations


We propose a novel criterion for evaluating user input for human-robot interfaces for known tasks. We use the mode insertion gradient (MIG)—a tool from hybrid control theory—as a filtering criterion that instantaneously assesses the impact of user actions on a dynamic system over a time window into the future. As a result, the filter is permissive to many chosen strategies, minimally engaging, and skill-sensitive—qualities desired when evaluating human actions. Through a human study with 28 healthy volunteers, we show that the criterion exhibits a low, but significant, negative correlation between skill level, as estimated from task-specific measures in unassisted trials, and the rate of controller intervention during assistance. Moreover, a MIG-based filter can be utilized to create a shared control scheme for training or assistance. In the human study, we observe a substantial training effect when using a MIG-based filter to perform cart-pendulum inversion, particularly when comparing improvement via the RMS error measure. Using simulation of a controlled spring-loaded inverted pendulum (SLIP) as a test case, we observe that the MIG criterion could be used for assistance to guarantee either task completion or safety of a joint human-robot system, while maintaining the system’s flexibility with respect to user-chosen strategies.

Original languageEnglish (US)
Title of host publicationRobotics
Subtitle of host publicationScience and Systems XIV
EditorsHadas Kress-Gazit, Siddhartha S. Srinivasa, Tom Howard, Nikolay Atanasov
PublisherMIT Press Journals
ISBN (Print)9780992374747
StatePublished - 2018
Event14th Robotics: Science and Systems, RSS 2018 - Pittsburgh, United States
Duration: Jun 26 2018Jun 30 2018

Publication series

NameRobotics: Science and Systems
ISSN (Electronic)2330-765X


Conference14th Robotics: Science and Systems, RSS 2018
Country/TerritoryUnited States

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Control and Systems Engineering
  • Electrical and Electronic Engineering


Dive into the research topics of 'Online User Assessment for Minimal Intervention During Task-Based Robotic Assistance'. Together they form a unique fingerprint.

Cite this