Non-monotonic Spatial Reasoning for Safety Analysis in Construction

We present a new approach based on spatial reasoning in Answer Set Programming (ASP), and a prototype software tool, for automatically evaluating construction safety compliance of real-world Building Information Models (BIM) that have both a geometric component and temporal component in the form of a construction plan and schedule (4D BIM). In the 4D BIM domain, geometries of building objects are large and complex making it highly impractical to represent geometries as ASP facts, unoptimised spatial reasoning can be prohibitively slow, and rounding errors in floating point arithmetic often result in logical contradictions. Our novel framework addresses these challenges by integrating a specialised geometry database, built-in spatial optimisations, and support for real arithmetic solving. We empirically evaluate our prototype software tool on two large 4D BIM models from real buildings to demonstrate the practicality and scalability of our new framework to real-world workplace hazard prevention tasks in construction safety-in-design analysis.

[1]  Charles M. Eastman,et al.  Building Information Modeling (BIM) and Safety: Automatic Safety Checking of Construction Models and Schedules , 2013 .

[2]  Jochen Teizer,et al.  Right-time vs real-time pro-active construction safety and health system architecture , 2016 .

[3]  Giovambattista Ianni,et al.  An ASP System with Functions, Lists, and Sets , 2009, LPNMR.

[4]  Jochen Teizer,et al.  A case study on automated safety compliance checking to assist fall protection design and planning in building information models , 2013 .

[5]  Markus König,et al.  Applying rule-based model-checking to construction site layout planning tasks , 2019 .

[6]  V. S. Costa,et al.  Theory and Practice of Logic Programming , 2010 .

[7]  Carl P. L. Schultz,et al.  Non-Monotonic Spatial Reasoning with Answer Set Programming Modulo Theories , 2017, Theory Pract. Log. Program..

[8]  Carl P. L. Schultz,et al.  ASPMT(QS): Non-Monotonic Spatial Reasoning with Answer Set Programming Modulo Theories , 2015, LPNMR.

[9]  Jochen Teizer,et al.  Ontology-based semantic modeling of construction safety knowledge: Towards automated safety planning for job hazard analysis (JHA) , 2015 .

[10]  Carl P. L. Schultz,et al.  lambdaProlog(QS): Functional Spatial Reasoning in Higher Order Logic Programming (Short Paper) , 2019, COSIT.

[11]  Martin Gebser,et al.  Theory Solving Made Easy with Clingo 5 , 2016, ICLP.

[12]  Torsten Schaub,et al.  ASP modulo CSP: The clingcon system , 2012, Theory and Practice of Logic Programming.

[13]  Joohyung Lee,et al.  System aspmt2smt: Computing ASPMT Theories by SMT Solvers , 2014, JELIA.

[14]  Carl P. L. Schultz,et al.  The shape of empty space: Human-centred cognitive foundations in computing for spatial design , 2012, 2012 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC).

[15]  Simona Perri,et al.  External Computations and Interoperability in the New DLV Grounder , 2017, AI*IA.

[16]  Nikolaj Bjørner,et al.  Z3: An Efficient SMT Solver , 2008, TACAS.

[17]  Miroslaw Truszczynski,et al.  Answer set programming at a glance , 2011, Commun. ACM.

[18]  Charles M. Eastman,et al.  BIM-based fall hazard identification and prevention in construction safety planning , 2015 .

[19]  John A. Gambatese,et al.  Owners’ Role in Facilitating Prevention through Design , 2017 .