Simulation Framework

Simulation frameworks are computational tools designed to model complex systems, enabling researchers to test hypotheses, evaluate algorithms, and explore design spaces without the cost and risk of real-world experimentation. Current research emphasizes the development of modular and extensible frameworks, often incorporating machine learning algorithms (like reinforcement learning and neural ODEs) and leveraging existing platforms (such as ROS2, PyTorch, and AirSim). These advancements are significantly impacting various fields, from autonomous vehicle development and robotics to healthcare, enabling more efficient research and the design of safer, more robust systems.