A declarative spatial reasoning system based on Answer Set Programming (ASP) to query, analyse, validate, and optimise large-scale Building Information Models (BIM).
ASP4BIM is a logic-based reasoning framework specifically designed for implicit, incomplete human spatial knowledge and numerous, complex real-world spatial data.
ASP4BIM can be viewed as a melting pot for
- natural language statements describing a person's experiences and behaviour in the built environment that are often ambiguous and vague by nature,
- digital building models with rich semantics and complex geometries that are posssibly inaccurate and imprecise,
- domain-specific rules and constraints about human-centric design concepts such as privacy, accessibility, safety, navigability, audibility, etc.
ASP4BIM is implemented via clingo's Python API (https://potassco.org/clingo/python-api/5.4/) and uses state-of-the-art geometry libraries for spatial computations.
- Install clingo via
conda
conda install -c potassco clingo
We use clingo version 5.4.0 with Python 3.7.4
- We use Clipper to compute Boolean operations on polygons
Install the Python wrapper via pip
pip install pyclipper
Alternatively, one can use PyMesh for polyhedrons
ASP4BIM is currently being developed within the scope of my PhD project Intelligent Software, Healing Environment at the Cyber-Physical Systems group, Aarhus University, Denmark. ASP4BIM is largely based on prototype systems CLP(QS) and ASPMT(QS), and draws from many theoretical and practical contributions of the modern ASP system clingo.
The data used in the source codes, courtesy of Assoc.Prof. Jochen Teizer, Dr. Olga Golovina, and Asst.Prof. Aliakbar Kamari, are for demonstration purposes only and strictly proprietary. I am also extremely grateful to my supervisors Asst.Prof. Carl Schultz and Prof. Peter Gorm Larsen for their guidance, and the Independent Research Fund Denmark (DFF) for their financial support.
Please kindly refer to the following research papers for a deep-dive into Declarative Spatial Reasoning, Answer Set Programming, and Building Information Modelling.
[1] Gebser, M., Kaminski, R., Kaufmann, B., Ostrowski, M., Schaub, T., & Wanko, P. (2016). Theory solving made easy with clingo 5. In Technical Communications of the 32nd International Conference on Logic Programming (ICLP 2016). Open Access Series in Informatics (OASIcs). Schloss Dagstuhl–Leibniz-Zentrum für Informatik. https://doi.org/10.4230/OASIcs.ICLP.2016.2
[2] Li, B., & Schultz, C. (2024). Clingo2DSR – A clingo-based software system for declarative spatial reasoning. Spatial Cognition & Computation, 25(1), 69–119. https://doi.org/10.1080/13875868.2024.2324875