Toward risk aware mission planning for Autonomous Underwater Vehicles

Abstract

Long range and high endurance Autonomous Underwater Vehicles such as gliders enable sustained oceanographic sampling at larger time-scales and much lower operational costs compared to traditional ship-based sampling methods. While most path-planning methods for AUVs optimize paths with respect to efficiency, obstacle avoidance, and control they do not explicitly address the issue of finding the safest possible path when considering risks such as shipping traffic and bathymetry. In coastal regions with high shipping traffic, reducing collision risk at the path planning stage, at the expense of efficiency, is a worthwhile trade-off. We propose a method of building risk maps using historical data from the Automated Information System. These are used to plan minimum risk paths between a specified start and goal location, while avoiding obstacles, using an algorithm based on A * search. Our planner incorporates the uncertainty in dead-reckoning without explicitly considering the effect of ocean currents. We compare the relative risk of paths produced by our method when compared to a shortest-path planner which does not take risk into account, and show that our methods performs significantly better, while producing competitive paths lengths.

Towards improving mission execution for autonomous gliders with an ocean model and kalman filter

“…However, we must be mindful that the vehicle will spend twice as much time on the surface in the case of T = 3 hours than when T = 8 hours. To make an informed decision regarding the safety of the vehicle over the course of a one-month deployment when surfacing every 3 hours, the method presented here could be combined with the risk-aware mission planning presented in [21].…”

Learning uncertainty models for reliable operation of Autonomous Underwater Vehicles

“…Predictions of ocean currents have previously been used by several research groups to improve the navigation capabilities of autonomous vehicles and improve the safety of their operation [7], [8]. Lower bounds on navigation error have also been derived to estimate the path following performance of underwater vehicles [9].…”

Spiraling motion of underwater gliders: Modeling, analysis, and experimental results

“…The spiraling motion will offer a low energy turning behavior, serving as an alternative to fast turning behaviors that involve active propulsion. Path planning methods developed in Isern-Gonzá lez et al (2011) and Pereira et al (2011) may also benefit from an understanding of the spiraling motion so that a glider can be temporarily parked at a spot against a strong ocean current. The paper is organized as follows.…”