Design and Implementation of Navigation and Control for Autonomous Underwater Vehicles
Abstract
Autonomous Underwater Vehicles (AUVs) play a vital role in a wide range of underwater applications, including scientific research, underwater mapping, and surveillance. One of the key challenges in AUV development is the design of an efficient and robust navigation system that enables precise control over speed and orientation. This paper presents a comprehensive approach for designing and implementing a navigation system incorporating both speed and orientation control for AUVs. The navigation system begins with the integration of a suite of sensors, including depth sensors, inertial measurement units (IMUs), and Global Positioning System (GPS) receivers, to provide accurate and real-time information about the AUV's position, attitude, and velocity. This sensor fusion technique enables the estimation of the AUV's state with high reliability and accuracy. For speed control, a dynamic model of the AUV is developed, considering factors such as hydrodynamics, thruster characteristics, and external disturbances. Based on this model, a model-based controller is designed to regulate the AUV's speed, ensuring precise velocity tracking and disturbance rejection. The controller utilizes feedback from the sensor suite to adjust the thruster inputs and maintain the desired speed. In addition to speed control, the navigation system incorporates orientation control to regulate the AUV's heading and yaw angle. A suitable controller is designed to enable accurate and stable orientation control, allowing the AUV to follow predefined paths or adapt to changing environmental conditions. This controller takes advantage of the IMU's measurements and utilizes feedback to adjust the thruster configurations and achieve the desired orientation. To validate the proposed navigation system, extensive simulations and experiments are conducted using a state-of-the-art AUV platform. The results demonstrate the effectiveness of the designed speed and orientation controllers in achieving precise and robust control performance under various operational scenarios and environmental conditions. The developed navigation system not only provides accurate and reliable control over the AUV's speed and orientation but also serves as a foundation for advanced tasks such as path planning, obstacle avoidance, and underwater mapping. The presented approach can be readily applied to a wide range of AUV platforms and has the potential to enhance the autonomy and operational capabilities of underwater robotic systems, contributing to the progress of underwater exploration and scientific research.
References
Carlucho, Ignacio, et al. "Adaptive low-level control of autonomous underwater vehicles using deep reinforcement learning." Robotics and Autonomous Systems 107 (2018): 71-86.
Hong, Eng You, Hong Geok Soon, and Mandar Chitre. "Depth control of an autonomous underwater vehicle, STARFISH." OCEANS'10 IEEE SYDNEY. IEEE, 2010.
Miller, Paul A., et al. "Autonomous underwater vehicle navigation." IEEE Journal of Oceanic Engineering 35.3 (2010): 663-678.
Valeriano-Medina, Yunier, et al. "Dynamic model for an autonomous underwater vehicle based on experimental data." Mathematical and Computer Modelling of Dynamical Systems 19.2 (2013): 175-200.
Refbacks
- There are currently no refbacks.

This work is licensed under a Creative Commons Attribution 3.0 License.