A Hierarchal Planning Framework for AUV Mission Management in a Spatio-Temporal Varying Ocean

The purpose of this paper is to provide a hierarchical dynamic mission planning framework for a single autonomous underwater vehicle (AUV) to accomplish task-assign process in a limited time interval while operating in an uncertain undersea environment, where spatio-temporal variability of the operating field is taken into account. To this end, a high level reactive mission planner and a low level motion planning system are constructed. The high level system is responsible for task priority assignment and guiding the vehicle toward a target of interest considering on-time termination of the mission. The lower layer is in charge of generating optimal trajectories based on sequence of tasks and dynamicity of operating terrain. The mission planner is able to reactively re-arrange the tasks based on mission/terrain updates while the low level planner is capable of coping unexpected changes of the terrain by correcting the old path and re-generating a new trajectory. As a result, the vehicle is able to undertake the maximum number of tasks with certain degree of maneuverability having situational awareness of the operating field. The computational engine of the mentioned framework is based on the biogeography based optimization (BBO) algorithm that is capable of providing efficient solutions. To evaluate the performance of the proposed framework, firstly, a realistic model of undersea environment is provided based on realistic map data, and then several scenarios, treated as real experiments, are designed through the simulation study. Additionally, to show the robustness and reliability of the framework, Monte-Carlo simulation is carried out and statistical analysis is performed. The results of simulations indicate the significant potential of the two-level hierarchical mission planning system in mission success and its applicability for real-time implementation

IDVD-based trajectory generator for autonomous underwater docking operations

This paper investigates capability and efficiency of utilizing the inverse dynamics in the virtual domain (IDVD) method to provide the real-time updates of feasible trajectory for an autonomous underwater vehicle (AUV) during underwater docking operations. The applicability of the IDVD method is examined for two scenarios. For the first scenario, referred to as an offline scenario, a nominal trajectory may be generated ahead of time based on a priori knowledge about the docking station (DS) pose (position and orientation). The second scenario, referred to as an online scenario, assumes some uncertainty in the DS pose; hence, the reference trajectory needs to be constantly recomputed in real time based on the updates about the DS pose. The offline scenario solution serves as a benchmark solution to check feasibility and optimality of generated trajectory subject to constraints on the states and controls. In particular, the offline solution can assist in making informed trade-off decisions between optimality of solution and computational efficiency. For the relatively simple offline scenario, the IDVD-method solution is compared with the Legendre–Gauss–Lobatto pseudo-spectral (LGLPS) method solution. The software-in-the-loop simulations and Monte Carlo trials are run for robustness assessment. Finally, the potential for the IDVD method to work online, in a closed-loop guidance system, is explored using a realistic cluttered operational simulation environment. Simulation results show that the IDVD-method based guidance system guarantees a reliable and efficient docking process by generating computationally efficient, feasible and ready to be tracked trajectories