Symbolic reasoning about unseen objects from multimodal sensory feedback for manipulation

Master Thesis (2020)
Author(s)

A.N. Helsloot (TU Delft - Mechanical Engineering)

Contributor(s)

M. Imre – Mentor (TU Delft - Learning & Autonomous Control)

Carlos Hernández – Mentor (TU Delft - Robot Dynamics)

Jens Kober – Mentor (TU Delft - Learning & Autonomous Control)

Joris Sijs – Graduation committee member (TNO)

Faculty
Mechanical Engineering
Copyright
© 2020 Arthur Helsloot
More Info
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Publication Year
2020
Language
English
Copyright
© 2020 Arthur Helsloot
Graduation Date
11-12-2020
Awarding Institution
Delft University of Technology
Faculty
Mechanical Engineering
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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.

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