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Main Author: Oh, Jaehong
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2506.13149
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author Oh, Jaehong
author_facet Oh, Jaehong
contents This paper presents SEGO (Semantic Graph Ontology), a cognitive mapping architecture designed to integrate geometric perception, semantic reasoning, and explanation generation into a unified framework for human-centric collaborative robotics. SEGO constructs dynamic cognitive scene graphs that represent not only the spatial configuration of the environment but also the semantic relations and ontological consistency among detected objects. The architecture seamlessly combines SLAM-based localization, deep-learning-based object detection and tracking, and ontology-driven reasoning to enable real-time, semantically coherent mapping.
format Preprint
id arxiv_https___arxiv_org_abs_2506_13149
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Cognitive Synergy Architecture: SEGO for Human-Centric Collaborative Robots
Oh, Jaehong
Robotics
Systems and Control
This paper presents SEGO (Semantic Graph Ontology), a cognitive mapping architecture designed to integrate geometric perception, semantic reasoning, and explanation generation into a unified framework for human-centric collaborative robotics. SEGO constructs dynamic cognitive scene graphs that represent not only the spatial configuration of the environment but also the semantic relations and ontological consistency among detected objects. The architecture seamlessly combines SLAM-based localization, deep-learning-based object detection and tracking, and ontology-driven reasoning to enable real-time, semantically coherent mapping.
title Cognitive Synergy Architecture: SEGO for Human-Centric Collaborative Robots
topic Robotics
Systems and Control
url https://arxiv.org/abs/2506.13149