AUV trajectory optimization with hydrodynamic forces for Icy Moon Exploration

TL;DR

This work tackles energy-efficient navigation of an underactuated AUV (DeepLeng) intended for under-ice exploration on icy moons like Europa. It develops a Direct Transcription-based Trajectory Optimization that explicitly accounts for hydrostatic and hydrodynamic effects, coupled with a time-varying LQR that stabilizes execution around the computed reference. Through Drake simulations of three challenging maneuvers—pole balancing, quarter helices, and steep elevation—under thruster limits $F_{min} = -70\,\mathrm{N}$ and $F_{max} = 70\,\mathrm{N}$, the results demonstrate the framework’s ability to generate feasible, aggressive trajectories while respecting hydrodynamic constraints. The study highlights the critical role of accurate hydrodynamic modeling and suggests online model adaptation to cope with unknown ocean properties for robust Europa mission planning and execution.

Abstract

To explore oceans on ice-covered moons in the solar system, energy-efficient Autonomous Underwater Vehicles (AUVs) with long ranges must cover enough distance to record and collect enough data. These usually underactuated vehicles are hard to control when performing tasks such as vertical docking or the inspection of vertical walls. This paper introduces a control strategy for DeepLeng to navigate in the ice-covered ocean of Jupiter's moon Europa and presents simulation results preceding a discussion on what is further needed for robust control during the mission.

Figures (8)

• Figure 1: DeepLeng AUV demonstrating the vectored thrust during under-ice deployment in Abisko, Sweden
• Figure 2: Pan-tilt unit of DeepLeng
• Figure 3: The position and orientation of the pole balancing trajectory
• Figure 4: The position and orientation of the quarterhelix trajectory
• Figure 5: The position and orientation of the steep elevation trajectory