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From Human to Height-Field: Predictive Shotcrete Simulation with a Physics-Informed Particle System

  • Swiss Federal Institute of Technology in Lausanne

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

This paper presents a validation study of a real-time shotcrete simulation model based on a physics-informed particle system. The model emulates concrete spray dynamics by replaying empirically recorded nozzle trajectories from expert and novice operators in a controlled virtual environment. We evaluate its ability to capture skill-related differences in key sprayability metrics, including material adhesion, rebound, and cohesive failure. The results reveal statistically significant distinctions between expert and novice performance, confirming the model’s sensitivity to operator expertise. The simulation also demonstrated strong repeatability and robustness despite inherent stochasticity. While the lack of physical ground truth and the absence of the material's lateral motion are noted limitations, the findings support the model's potential use in training and skill assessment. Future work will focus on improving material modeling to enhance realism and predictive accuracy.
Original languageEnglish
Title of host publication2025 IEEE International Conference on Advanced Robotics (ICAR)
PublisherIEEE
Publication dateDec 2025
Pages826-832
ISBN (Electronic)979-8-3315-7809-1
DOIs
Publication statusPublished - Dec 2025
Event2025 International Conference on Advanced Robotics (ICAR) - San Juan, Argentina
Duration: 2. Dec 20255. Dec 2025

Conference

Conference2025 International Conference on Advanced Robotics (ICAR)
Country/TerritoryArgentina
CitySan Juan
Period02/12/202505/12/2025
SeriesProceedings of the International Conference on Advanced Robotics (ICAR)
ISSN2374-3255

Keywords

  • Shotcrete Simulation
  • Particle System
  • Optical Motion Capture
  • Nozzle Operator Expertise
  • Simulation Validation

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