Cited by 1Logic, Reasoning, and KnowledgeData Management and AlgorithmsConstraint Satisfaction and Optimization

Spatial Reasoner: A 3D Inference Pipeline for XR Applications

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Hasler, Steven, Ackermann, Philipp·2025·2025 International Conference on Intelligent Computing and Virtual & Augmented Reality Simulations (ICVARS)

Abstract

Modern extended reality (XR) systems provide rich analysis of image data and fusion of sensor input and demand ARlVR applications that can reason about 3D scenes in a semantic manner. We present a spatial reasoning framework that bridges geometric facts with symbolic predicates and relations to handle key tasks such as determining how 3D objects are arranged among each other (‘on’, ‘behind’, ‘near’, etc.), Its foundation relies on oriented 3D bounding box representations, enhanced by a comprehensive set of spatial predicates, ranging from topology and connectivity to directionality and orientation, expressed in a formalism related to natural language. The derived predicates form a spatial knowledge graph and, in combination with a pipeline-based inference model, enable spatial queries and dynamic rule evaluation. Implementations for client- and server-side processing demonstrate the framework's capability to efficiently translate geometric data into actionable knowledge, ensuring scalable and technology-independent spatial reasoning in complex 3D environments. The Spatial Reasoner framework is fostering the creation of spatial ontologies, and seamlessly integrates with and therefore enriches machine learning, natural language processing, and rule systems in XR applications.

Integrity signals

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Crossref · 10.1109/icvars66454.2025.11198690

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Research works printed but not linked: 4

  1. Zuliansyah, 2008, 3d topological relations for 3d spatial analysis, CIS. IEEE, 753
  2. Forrest, 2023, Spatial SQL: A Practical Approach to Modern GIS Using SQL
  3. Car, 2023, OGC GeoSPARQL - A Geographic Query Language for RDF Data
  4. Muff, 2022, A framework for context-dependent augmented reality applications using machine learning and ontological reasoning

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Authors
Hasler, S., & Ackermann, P.
Affiliations
  • ZHAW Zurich University of Applied Sciences, School of Engineering,Winterthur,Switzerland
  • ZHAW Zurich University of Applied Sciences (CH)
Venue
2025 International Conference on Intelligent Computing and Virtual & Augmented Reality Simulations (ICVARS)
Publisher
IEEE
Published
2025-07-25
Pages
121-130
OpenAlex
W4415285249
Cited by
1
References
17
Citations by year
2026: 1
FWCI
1.06
Type
conference paper
Language
en
Locations
Zürcher Hochschule für Angewandte Wissenschaften digital collection (Zurich University of Applied Sciences) (submittedVersion, cc-by-nc-nd)
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Logic, Reasoning, and Knowledge
  • Physical Sciences › Computer Science › Signal Processing › Data Management and Algorithms
  • Physical Sciences › Computer Science › Computer Networks and Communications › Constraint Satisfaction and Optimization
Keywords
spatial reasoning, extended reality, 3D scene understanding, spatial predicates, spatial ontology, spatial queries, rule-based reasoning

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