Modeling a robust control system with a precise GPS-based state estimation capability in simulation can be useful in field navigation applications as it allows for testing and validation in a controlled environment. This testing process would enable navigation systems to be developed and optimized in simulation with direct transferability to real-world scenarios. The multi-physics simulation engine Chrono allows for the creation of scenarios that may be difficult or dangerous to replicate in the field, such as extreme weather or terrain conditions. Autonomy Research Testbed (ART), a specialized robotics algorithm testbed, is operated in conjunction with Chrono to develop an MPC control policy as well as an EKF state estimator. This platform enables users to easily integrate custom algorithms in the autonomy stack. This model is initially developed and used in simulation and then tested on a twin vehicle model in reality, to demonstrate the transferability between simulation and reality (also known as Sim2Real).

翻译：在仿真中构建具备精确GPS状态估计能力的鲁棒控制系统，对野外导航应用具有重要意义，因为这可以在受控环境中进行测试与验证。该测试流程使导航系统能够在仿真环境中开发优化，并直接迁移至真实场景。多物理场仿真引擎Chrono能够创建难以或危险在野外复现的场景（如极端天气或地形条件）。自主研究测试平台（ART）作为专业机器人算法测试平台，与Chrono协同运行，用于开发MPC控制策略及EKF状态估计器。该平台使用户能够轻松在自主堆栈中集成自定义算法。该模型首先在仿真中开发并使用，随后在真实世界的双车模型上进行测试，以验证仿真与真实环境之间的可迁移性（即Sim2Real）。