Probability of Mobility for Mission Planning of Autonomous Ground Vehicles at “High Stress” Environments

Project began 2019 and was completed 2021.

Developing a Next Generation NATO Reference Mobility Model (NG-NRMM) is critical to vehicle mobility performance prediction and mission planning. The objective of this research is to develop a systematic framework for mission planning of Autonomous Ground Vehicles (AGVs) at “high stress” environments considering heterogeneous uncertainty sources. The “high stress” term refers to rough off-road terrain (e.g. abrupt changes in elevation), severe soil conditions, and/or extreme operating conditions (e.g. high speed).

It is still very challenging to accurately predict the mobility at “high stress” environments for the following reasons:

1. The physics of vehicle mobility is too complicated to be fully understood and quantified at “high stress” environments.
2. There is large uncertainty in the mobility prediction of physics-based simulation models due to modeling simplifications and assumptions, challenging terrain conditions, limited knowledge on the interactions between vehicle and terrain, and heterogeneous uncertainty sources in vehicle systems and terrain properties.
3. Replacing the physics-based simulation model with a Kriging surrogate model (i.e. Kriging-based stochastic mobility map) will not eliminate/reduce the aforementioned uncertainty sources.

The objectives of this research are to account for heterogeneous uncertainty sources to improve the prediction confidence in developing a NG-NRMM, and to develop a mission planning approach for operation in “high stress” environments. The objectives will be achieved by integrating physics-based simulations, soil and topographic maps, and lab/field tests.

Journal Publications:

Jiang, C., Liu, Y., Mourelatos, Z., Gorsich, D., Fu, Y., and Hu, Z., “Efficient Reliability-Based Mission Planning of Off-Road Autonomous Ground Vehicles using An Outcrossing Approach”, ASME Journal of Mechanical Design, 2022, 144(4).

Jiang, C., Hu, Z., Mourelatos, Z., Gorsich, D., Jayakumar, P., Fu, Y., and Majcher, M., “R2-RRT*: Reliability-Based Robust Mission Planning of Off-Road Autonomous Ground Vehicle Under Uncertain Terrain Environment”, IEEE Transactions on Automation Science and Engineering, vol. 19, no. 2, pp. 1030-1046, April 2022, doi: 10.1109/TASE.2021.3050762.

Jiang, C., Hu, Z., Liu, Y., Mourelatos, Z., Gorsich, D., Jayakumar, P., “A Sequential Calibration and Validation Framework for Model Uncertainty Quantification and Reduction”, Computer Methods in Applied Mechanics and Engineering, 2020, 368, 113172.

Papadimitriou, D., Mourelatos, Z., Hu, Z., “Reliability Analysis and Random Vibration of Nonlinear Systems using the Adjoint Method and Projected Differentiation”, ASME Journal of Mechanical Design, Jun 2021, 143(6): 061705 , DOI: doi.org/10.1115/1.4048958.

Liu, Y., Jiang, C., Mourelatos, Z., Gorsich, D., Jayakumar, P., Fu, Y., Hu, Z., “Simulation-Based Mission Mobility Reliability Analysis of Off-Road Ground Vehicles”, ASME Journal of Mechanical Design, 2020, DOI: doi.org/10.1115/1.4048314.

Hu, Z., Mourelatos, Z., Gorsich, D., Paramsothy, J., and Majcher, M., “Testing Design Optimization for Uncertainty Reduction in Generating Off-Road Mobility Map Using a Bayesian Approach”, ASME Journal of Mechanical Design, 2020, 142 (2).

Moustafa, K., Hu, Z., Mourelatos, Z., Baseski, I., and Majcher, M., “Resource Allocation for System Reliability Assessment Using Accelerated Life Testing”, ASME Journal of Mechanical Design, 2020, 142 (3).

Papadimitriou, D., Mourelatos, Z. P., Patil, S., Hu, Z., Tsianika, V., and Geroulas, V., “Reliability Analysis of Nonlinear Vibratory Systems Under Non-Gaussian Loads Using a Sensitivity-Based Propagation of Moments,” ASME Journal of Mechanical Design 2020, 142 (6).

Liu, Y., Zhao, Y., Hu, Z., Mourelatos, Z. P., and Papadimitriou, D., “Collision-Avoidance Reliability Analysis of Automated Vehicle Based on Adaptive Surrogate Modeling,” ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering, 2019 5(2), (2019 Editors’ Choice Best Paper Award).

References:

1. McCullough, M., Jayakumar, P., Dasch, J., and Gorsich, D., 2017, “The Next Generation NATO Reference mobility model development,” Journal of Terramechanics, 73, pp. 49-60.
2. Recuero, A., Serban, R., Peterson, B., Sugiyama, H., Jayakumar, P., and Negrut, D., 2017, “A high-fidelity approach for vehicle mobility simulation: Nonlinear finite element tires operating on granular material,” Journal of Terramechanics, 72, pp. 39-54.
3. Serban, R., Olsen, N., Negrut, D., Recuero, A., and Jayakumar, P., “A co-simulation framework for high-performance, high-fidelity simulation of ground vehicle-terrain interaction,” Proc. Conference: NATO AVT-265 Specialists’ Meeting, Vilnius, Lithuania (May 2017), Paper Number STO-MP-AVT-265.
4. Choi, K., Gaul, N., Jayakumar, P., Wasfy, T., and Funk, M., “Framework of Reliability-Based Stochastic Mobility Map for Next Generation NATO Reference Mobiity Model,” Journal of Computational and Nonlinear Dynamics, doi:10.1115/1.4041350.

#1.A90