Path Following and Collision Avoidance of a Ribbon-Fin Propelled Underwater Biomimetic Vehicle-Manipulator System

Area of Science:

• Robotics
• Marine Engineering
• Control Systems

Background:

• Underwater vehicle-manipulator systems (UBVMS) face challenges in navigation due to complex dynamics and environmental uncertainties.
• Simultaneous path following and dynamic obstacle avoidance are critical for safe and efficient UBVMS operation.
• Existing control methods often struggle with model uncertainties and real-time dynamic obstacle prediction.

Purpose of the Study:

• To develop and validate a control scheme for UBVMS that achieves accurate path following and effective dynamic obstacle avoidance.
• To enhance the robustness of the control system against model uncertainties and external disturbances.
• To improve the prediction of dynamic obstacle positions for proactive collision avoidance.

Main Methods:

• A nonlinear model predictive control (NMPC) framework was implemented for integrated path following and obstacle avoidance.
• Improved extended state observers (IESOs) were utilized to estimate and compensate for model uncertainties and disturbances.
• A Kalman filter was combined with a priori estimation to predict the short-term positions of dynamic obstacles, accounting for state estimator uncertainty.

Main Results:

• The proposed NMPC scheme effectively tracked reference paths while simultaneously avoiding dynamic obstacles.
• The use of IESOs significantly improved robustness by accurately estimating and mitigating uncertainties and disturbances.
• The integrated Kalman filter and a priori estimation provided reliable short-term obstacle predictions, enhancing safety.

Conclusions:

• The developed control strategy demonstrates high performance and robustness for UBVMS in complex underwater environments.
• The method successfully addresses the dual challenges of path following and dynamic obstacle avoidance under uncertain conditions.
• Simulations and experimental results confirm the validity and practical applicability of the proposed approach for UBVMS navigation.