Publication
Title
Structured exploration through instruction enhancement for object navigation
Author
Abstract
Finding an object of a specific class in an unseen environment remains an unsolved navigation problem. Hence, we propose a hierarchical learning-based method for object navigation. The top-level is capable of high-level planning, and building a memory on a floorplan-level (e.g., which room makes the most sense for the agent to visit next, where has the agent already been?). While the lower-level is tasked with efficiently navigating between rooms and looking for objects in them. Instructions can be provided to the agent using a simple synthetic language. The toplevel intelligently enhances the instructions in order to make the overall task more tractable. Language grounding, mapping instructions to visual observations, is performed by utilizing an additional separate supervised trained goal assessment module. We demonstrate the effectiveness of our method on a dynamic configurable domestic environment.
Language
English
Source (book)
34th Benelux Conference on Artificial Intelligence and the 31 Belgium Dutch Conference on Machine Learning (BNAIC/BENELEARN 2022), 7-9 November, 2022, Mechelen, Belgium
Publication
2022
Volume/pages
p. 1-16
Full text (open access)
UAntwerpen
Faculty/Department
Research group
Project info
A Connected Brain-sized network – Design of a distributed connectivity layer for combining different heterogeneous deep learning systems.
Publication type
Subject
Affiliation
Publications with a UAntwerp address
External links
Source file
Record
Identifier
Creation 12.12.2023
Last edited 17.06.2024
To cite this reference