Trajectory optimization of an unmanned aerial–aquatic rotorcraft navigating between air and water

Unmanned aerial–aquatic vehicles are a new type of aircraft that can navigate in air and underwater. An unmanned rotorcraft (UAAR) is introduced to complete the task navigating between underwater, trajectory optimization problem for this focused on study. The dynamics four-axle with eight rotors operating underwater described. On basis, model established, wherein constraints control variables states different media included. index denoted as weighted sum terminal states. In view weakness teaching- learning-based (TLBO) algorithm, formula updating individual grade teaching process modified. Thus, ensures algorithm avoids converging at local optimum improves solution quality. Finally, an improved TLBO (ITLBO)-based method UAAR water developed. discretized respect height set Chebyshev collocation points reduce error states, values other heights obtained via interpolation. simulation studies, ITLBO-based exhibits better performance terms optimizing when compared two algorithms. Furthermore, effects distribution number results analyzed.