Next Article in Journal
Deployment Environment for a Swarm of Heterogeneous Robots
Previous Article in Journal
Towards Bio-Inspired Chromatic Behaviours in Surveillance Robots
Article Menu

Export Article

Open AccessArticle
Robotics 2016, 5(4), 21; doi:10.3390/robotics5040021

Towards an Explanation Generation System for Robots: Analysis and Recommendations

1
Department of Computer Science, The University of Auckland, Auckland 1010, New Zealand
2
Electrical and Computer Engineering, The University of Auckland, Auckland 1010, New Zealand
*
Author to whom correspondence should be addressed.
Academic Editor: Huosheng Hu
Received: 10 May 2016 / Revised: 29 August 2016 / Accepted: 26 September 2016 / Published: 13 October 2016
View Full-Text   |   Download PDF [585 KB, uploaded 13 October 2016]   |  

Abstract

A fundamental challenge in robotics is to reason with incomplete domain knowledge to explain unexpected observations and partial descriptions extracted from sensor observations. Existing explanation generation systems draw on ideas that can be mapped to a multidimensional space of system characteristics, defined by distinctions, such as how they represent knowledge and if and how they reason with heuristic guidance. Instances in this multidimensional space corresponding to existing systems do not support all of the desired explanation generation capabilities for robots. We seek to address this limitation by thoroughly understanding the range of explanation generation capabilities and the interplay between the distinctions that characterize them. Towards this objective, this paper first specifies three fundamental distinctions that can be used to characterize many existing explanation generation systems. We explore and understand the effects of these distinctions by comparing the capabilities of two systems that differ substantially along these axes, using execution scenarios involving a robot waiter assisting in seating people and delivering orders in a restaurant. The second part of the paper uses this study to argue that the desired explanation generation capabilities corresponding to these three distinctions can mostly be achieved by exploiting the complementary strengths of the two systems that were explored. This is followed by a discussion of the capabilities related to other major distinctions to provide detailed recommendations for developing an explanation generation system for robots. View Full-Text
Keywords: cognitive architectures; diagnosis; explanation generation; human-robot collaboration; human-robot interaction; knowledge representation; plan understanding; scene explanation cognitive architectures; diagnosis; explanation generation; human-robot collaboration; human-robot interaction; knowledge representation; plan understanding; scene explanation
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Meadows, B.; Sridharan, M.; Colaco, Z. Towards an Explanation Generation System for Robots: Analysis and Recommendations. Robotics 2016, 5, 21.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Robotics EISSN 2218-6581 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top