Self-Explainable Robots in Remote Environments

Francisco J. Chiyah Garcia, Simón C. Smith, José Lopes, Subramanian Ramamoorthy, Helen Hastie

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

Abstract / Description of output

As robots and autonomous systems become more adept at handling complex scenarios, their underlying mechanisms also become increasingly complex and opaque. This lack of transparency can give rise to unverifiable behaviours, limiting the use of robots in a number of applications including high-stakes scenarios, e.g. self-driving cars or first responders. In this paper and accompanying video, we present a system that learns from demonstrations to inspect areas in a remote environment and to explain robot behaviour. Using semi-supervised learning, the robot is able to inspect an offshore platform autonomously, whilst explaining its decision process both through both image-based and natural language-based interfaces.
Original languageEnglish
Title of host publicationCompanion of the 2021 ACM/IEEE International Conference on Human-Robot Interaction (HR '21 Companion)
PublisherACM Association for Computing Machinery
Number of pages3
ISBN (Print)9781450382908
Publication statusPublished - 8 Mar 2021
Event16th ACM/IEEE International Conference on Human-Robot Interaction - Virtual Conference
Duration: 9 Mar 202111 Mar 2021


Conference16th ACM/IEEE International Conference on Human-Robot Interaction
Abbreviated titleHRI 2021
CityVirtual Conference
Internet address

Keywords / Materials (for Non-textual outputs)

  • Explainable robot
  • semi-supervised learning
  • autonomous control
  • transparent interfaces
  • remote location
  • NLG


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