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Navigate to remember: a declarative memory model for incremental semantic mapping

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Biologically inspired computational techniques play a crucial role in robotic cognition. Artificial learning agents and robots that interact in complex environments must constantly acquire and refine knowledge over long periods of time. In this paper, we propose a novel recurrent neural architecture that mimics humans’ declarative memory system for continuously generating a cognitive map during robot navigation. The proposed method termed as Declarative Memory Adaptive Recurrent Model (DM-ARM), and consists of three hierarchical memory courses: (i) Working Memory, (ii) Episodic Memory and (iii) Semantic Memory layer. Each memory layer comprises a self-organizing adaptive recurrent incremental network (SOARIN) with a different learning task respectively. The Working Memory layer quickly clusters sensory information while the Episodic Memory layer learns fine-grained spatiotemporal relationships of clusters (temporal encoding). Both the memory layer learning is in an unsupervised manner. The Semantic Memory layer utilizes task-relevant cues to adjust the level of architectural flexibility and generate a semantic map that contains more compact episodic representations. The effectiveness of the proposed recurrent neural architecture is evaluated through a series of experiments. We implemented and validated our proposed work on the tasks of robot navigation.
Original languageEnglish
Title of host publicationIntelligent Robotics and Applications
Subtitle of host publication12th International Conference, ICIRA 2019, Shenyang, China, August 8–11, 2019, Proceedings, Part IV
EditorsHaibin Yu, Jinguo Liu, Lianquing Liu, Zhaojie Ju, Yuwang Liu, Dalin Zhao
PublisherSpringer
Chapter13
Pages142-153
Number of pages12
ISBN (Electronic)978-3-030-27538-9
ISBN (Print)978-3-030-27537-2
DOIs
Publication statusPublished - 3 Aug 2019
Event12th International Conference on Intelligent Robotics and Applications - Shenyang, China
Duration: 8 Aug 201911 Aug 2019

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume11743
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference12th International Conference on Intelligent Robotics and Applications
Abbreviated titleICIRA 2019
CountryChina
CityShenyang
Period8/08/1911/08/19

Documents

  • Chin_Navigate to Remember_ICIRA2019_463_final_v3-2

    Rights statement: This is a post-peer-review, pre-copyedit version of an article published in Intelligent Robotics and Applications. ICIRA 2019. The final authenticated version is available online at: http://dx.doi.org/10.1007/978-3-030-27538-9_13.

    Accepted author manuscript (Post-print), 780 KB, PDF document

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