In comparison to traditional fin and rudder propulsion devices, vector thruster autonomous underwater vehicles (AUVs) are renowned for their superior maneuverability, particularly at low or zero speeds. This study introduces a control strategy for vector thruster AUVs that employs deep reinforcement learning algorithms for three-dimensional random point and trajectory tracking. Simulation tests are conducted to investigate the motion of vector propelled AUVs. The utilization of deep reinforcement learning algorithms in this research demonstrates the potential of this approach in designing control strategies for vector thruster AUVs, ultimately enhancing maneuverability and autonomy in underwater exploration.
Research on Control Problems of vectored thruster AUVs with deep reinforcement learning
23.05.2024
782851 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Path guidance and attitude control of a vectored thruster AUV
Tema Archiv | 2004
|Design and Modeling of a Vectored Electrospray Thruster
AIAA | 2022
|Ion thruster for thrust vectored propulsion of a spacecraft
Europäisches Patentamt | 2024
|ION THRUSTER FOR THRUST VECTORED PROPULSION OF A SPACECRAFT
Europäisches Patentamt | 2021
|