TY - GEN
T1 - From Human to Height-Field: Predictive Shotcrete Simulation with a Physics-Informed Particle System
AU - Yazdi Samadi, Mohammad Reza
AU - Wu, Rui
AU - Gholami, Soheil
AU - Waspe, Ralf
AU - Muhammad, Ali
AU - Billard, Aude
AU - Schlette, Christian
PY - 2025/12
Y1 - 2025/12
N2 - 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.
AB - 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.
KW - Shotcrete Simulation
KW - Particle System
KW - Optical Motion Capture
KW - Nozzle Operator Expertise
KW - Simulation Validation
U2 - 10.1109/ICAR65334.2025.11338646
DO - 10.1109/ICAR65334.2025.11338646
M3 - Article in proceedings
T3 - Proceedings of the International Conference on Advanced Robotics (ICAR)
SP - 826
EP - 832
BT - 2025 IEEE International Conference on Advanced Robotics (ICAR)
PB - IEEE
T2 - 2025 International Conference on Advanced Robotics (ICAR)
Y2 - 2 December 2025 through 5 December 2025
ER -