Symbolic reasoning about unseen objects from multimodal sensory feedback for manipulation

Master thesis (2020)

Authors

A.N. Helsloot Mechanical Engineering

Contributors

M. Imre Learning & Autonomous Control - Mechanical, Maritime and Materials Engineering (supervisor 1)
Carlos Hernández Robot Dynamics - Mechanical, Maritime and Materials Engineering (supervisor 1)
J. Kober Learning & Autonomous Control - Mechanical, Maritime and Materials Engineering (supervisor 1)
Joris Sijs TNO (supervisor 2)
Faculty
Mechanical Engineering
Copyright: © 2020 Arthur Helsloot
Knowledge representation and reasoning Task planning Robot arm control Cognitive architecture
More Info
expand_more

Published Date

11-12-2020

Language

English

Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Faculty

Mechanical Engineering

Abstract

Robotically manipulating objects can be very challenging when not all of the environment can be fully observed, e.g. in environments which are physically and visually accessible from only a single side. By using multimodal sensory feedback and symbolic reasoning, conclusions can be drawn about the presence of objects that cannot be observed directly. This paper presents the Symbolic Reasoning for Partially Observable Environments (SyRePOE) system, which uses an ontology to maintain its world model and a reasoner to infer information about unobservable objects. SyRePOE is demonstrated in simulation and on a real robot, where it is tasked with stocking a retail shelf.