A hybrid skill parameterisation model combining symbolic and subsymbolic elements for introspective robots
- In the design of robot skills, the focus generally lies on increasing the flexibility and reliability of the robot execution process; however, typical skill representations are not designed for analysing execution failures if they occur or for explicitly learning from failures. In this paper, we describe a learning-based hybrid representation for skill parameterisation called an execution model, which considers execution failures to be a natural part of the execution process. We then (i) demonstrate how execution contexts can be included in execution models, (ii) introduce a technique for generalising models between object categories by combining generalisation attempts performed by a robot with knowledge about object similarities represented in an ontology, and (iii) describe a procedure that uses an execution model for identifying a likely hypothesis of a parameterisation failure. The feasibility of the proposed methods is evaluated in multiple experiments performed with a physical robot in the context of handle grasping, object grasping, and object pulling. The experimental results suggest that execution models contribute towards avoiding execution failures, but also represent a first step towards more introspective robots that are able to analyse some of their execution failures in an explicit manner.
Document Type: | Article |
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Language: | English |
Author: | Alex MitrevskiORCiD, Paul G. PlögerORCiD, Gerhard LakemeyerORCiD |
Parent Title (English): | Robotics and Autonomous Systems |
Volume: | 161 |
Article Number: | 104350 |
Number of pages: | 22 |
ISSN: | 0921-8890 |
DOI: | https://doi.org/10.1016/j.robot.2022.104350 |
Publisher: | Elsevier |
Date of first publication: | 2022/12/25 |
Funding: | This work has received support from the Bonn-Aachen International Center for Information Technology (b-it). |
Note: | This article is part of the special issue on Semantic Policy and Action Representations for Autonomous Robots. |
Note: | Abstract provided by the author. |
Keyword: | robot execution failures; robot introspection; skill execution models |
Departments, institutes and facilities: | Fachbereich Informatik |
Dewey Decimal Classification (DDC): | 0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik |
Entry in this database: | 2023/01/04 |