Disturbance-aware Motion Planning for Over-actuated Underwater Vehicles Exploiting Actuation Redundancy for High-fidelity 3D Reconstruction

2026-07-08

AI Summary

This study addresses the degradation of underwater imaging quality and 3D reconstruction accuracy caused by turbulence induced by high-thrust propellers on underwater robots disturbing seabed sediments. The work proposes a novel actuation-perception coupled motion planning framework that exploits actuator redundancy in over-actuated systems to optimize thrust allocation within the nullspace, actively suppressing fluid disturbances in regions of interest while satisfying motion constraints. A directionally attenuated wake surrogate model, grounded in actuator disk theory and validated via particle image velocimetry (PIV), is integrated with a real-time redundant allocator operating at 10 Hz (45 ms per iteration) for efficient computation. Experimental results from 440 trials demonstrate a 67% reduction in particle velocity within target areas, a 55% improvement in 3D reconstruction RMSE (1.9 ± 0.4 mm vs. 4.3 ± 1.8 mm), and a reconstruction success rate of 98.5%.

Abstract

Underwater robots often operate near delicate targets where high-power thrusters resuspend sediments and induce turbulence, degrading image quality at the sensor input. Conventional controllers optimize vehicle-centric objectives, such as tracking and stability, without accounting for the impact of actuation on sensing. We address this actuation-to-perception coupling by exploiting redundancy in over-actuated platforms. For an eight-thruster ROV, multiple thrust allocations can yield the same motion; we search this null space to minimize predicted disturbance in a task-relevant target region while enforcing motion constraints. Our method uses a control-oriented thruster-wake proxy derived from actuator-disk theory with directional attenuation and validated by PIV ($R^2 = 0.99$ near the wake axis; $R^2 > 0.82$ in the primary wake region), together with a real-time redundancy-resolving allocator running at 10 Hz (45 ms/solve). Across 440 trials, the approach reduces target-region particle velocity by 67% ($p < 0.001$), improves 3D reconstruction RMSE by 55% versus a disturbance-unaware baseline ($1.9 \pm 0.4$ mm vs. $4.3 \pm 1.8$ mm), and achieves a 98.5% reconstruction success rate. The framework supports autonomous scanning, which is quantitatively evaluated, and operator-assisted inspection, which is demonstrated in the supplementary materials.

Problem

• underwater vehicles
• actuation-to-perception coupling
• disturbance-aware motion planning
• 3D reconstruction
• actuation redundancy

Innovation

• actuation-to-perception coupling
• over-actuated underwater vehicle
• disturbance-aware motion planning
• thrust allocation redundancy
• high-fidelity 3D reconstruction