Quadrotor Model

Quadrotor modeling focuses on creating accurate and efficient representations of these unmanned aerial vehicles for control, navigation, and simulation purposes. Current research emphasizes developing robust models that account for uncertainties like wind disturbances and sensor noise, often employing techniques like factor graph optimization to tightly integrate positioning and control, and reinforcement learning algorithms for agile and adaptable flight control. These advancements are crucial for improving the reliability and performance of quadrotors in diverse applications, from autonomous delivery to search and rescue operations.