Current-sensitive path planning for an underactuated free-floating ocean Sensorweb

Abstract

This work investigates multiagent path planning in strong, dynamic currents using thousands of highly underactuated vehicles. We address the specific task of path planning for a global network of ocean-observing floats. These submersibles are typified by the Argo global network consisting of over 3000 sensor platforms. They can control their buoyancy to float at depth for data collection or rise to the surface for satellite communications. Currently, floats drift at a constant depth regardless of the local currents. However, accurate current forecasts have become available which present the possibility of intentionally controlling floats' motion by dynamically commanding them to linger at different depths. This project explores the use of these current predictions to direct float networks to some desired final formation or position. It presents multiple algorithms for such path optimization and demonstrates their advantage over the standard approach of constant-depth drifting. Fig 1. shows the configuration of Argo floats as of January, 2011. Some areas, such as the Sea of Japan, are congested by floats, and others, particularly near the poles, are unmonitored [2].

Stochastic Guidance of Buoyancy Controlled Vehicles under Ice Shelves using Ocean Currents

“…Much research exists related to path planning of underactuated marine vehicles in flow fields using ocean circulation models, including efficient long-range path planning of gliders in the presence of currents [16] [17], stationkeeping of gliders [18] and vertically profiling floats [19] near a location of interest, avoiding glider surfacing in dangerous locations [20], and optimizing float coverage across oceans [21]. Similar techniques exist for path planning of aerostats in wind fields, including Google's Project Loon using superpressure stratospheric balloons to provide internet connectivity [22], and planetary mission concepts for future Venus [23] and Titan [24] missions.…”

Energy-efficient path planning for fully propelled AUVs in congested coastal waters

“…their respective benchmark paths using (10). As part of the E(·) calculation using (1) to (5), the propulsion along the benchmark path is set at the lowest possible level needed to maintain desired bearing or k min , whichever is higher.…”

“…Majority of these systems are very sensitive to water current. Hence, significant research has been invested into effective path planning using ocean models [7]- [10].…”