Real-time Obstacle Avoidance for Underactuated Autonomous Underwater Vehicles in Unknown Vortex Sea Flow by the MDP Approach

摘要

A method for real-time collision avoidance for underactuated autonomous underwater vehicles (AUVs) in the sea environment with unknown obstacle configurations and unknown vortex sea flow is proposed. The proposed method is an application of the Markov-decision-process-(MDP) based motion planning method. It is essential to adopt the MDP-based method for managing both the kinematics and dynamics of an AUV affected by sea flow. The real-time obstacle avoidance needs re-planning when a new obstacle is discovered so that the AUV can find a suitable path around concave obstacles; however, MDP-based re-planning calculations require high computational power and are hard to be used in real time. In addition, it is impossible to know the whole distribution of the changing sea flow velocity in real time. Therefore, MDP-based re-planning calculation during the mission is not efficient. As a solution, the proposed method combines a rough re-planning considering only the geometrical properties of obstacles with rough target path tracking considering the kinematical and dynamical property of the AUV. Because there is no guarantee that the AUV can track the target path with high accuracy, the AUV is controlled to avoid collisions with obstacles at the same time. The rough target path tracking and obstacle avoidance is done using the result of off-line MDP based motion planning. The performance of the proposed method is examined by simulation of an AUV cruising in a vortex sea flow.