[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-84199-en":3,"doc-seo-84199-105":29,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":13,"seo_description":14,"update_tm":27,"read_time":28},84199,962075114765,"Quinn","https://ap-avatar.wpscdn.com/davatar_a8503ba1806abce46bf441b54a3ca4cd",8,"Research & Report","Disturbance-Aware Motion Planning for Over-Actuated Underwater Vehicles Exploiting Actuation Redundancy for High-Fidelity 3D Reconstruction","Underwater robots often work near delicate targets where thruster-induced turbulence resuspends sediments and degrades sensor image quality. This work tackles the actuation-to-perception coupling by exploiting redundancy in over-actuated vehicles. For an eight-thruster ROV, multiple thrust allocations produce the same motion, so a null-space search minimizes predicted disturbance in a task-relevant target region under motion constraints. A control-oriented thruster-wake proxy enables real-time redundancy allocation, validated by PIV, reducing target-region particle velocity by 67% and improving 3D reconstruction RMSE by 55%.","Disturbance-Aware Motion Planning for Over-Actuated Underwater Vehicles Exploiting Actuation Redundancy for High-Fidelity 3D Reconstruction  \nYuer Gao, Student Member, IEEE, Tongqing Xu, Qingyang Liu, and Yi Cai, Member, IEEE  \narXiv :2607 .07 139v 1 [ cs .RO] 8 Jul 2026  \nAbstract—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 (tracking and stability) without accounting for actuation’s impact on sensing. We address this actuation-to-perception coupling by exploiting redundancy in over-actuated platforms. For an eight-thruster ROV, multiple thrust allocations 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 actuatordisk theory with directional attenuation and validated by PIV (R2 = 0 .99 near the wake axis; R2 > 0.82 in the primary wake region), and 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 \u003C 0.001), improves 3D reconstruction RMSE by 55% versus a disturbanceunaware baseline (1 .9 ± 0.4 mm vs. 4.3 ± 1.8 mm), and achievesa 98.5% reconstruction success rate. The framework supports autonomous scanning (quantitatively evaluated) and operatorassisted inspection (demonstrated in supplementary materials).  \nIndex Terms—Over-actuated underwater vehicle, actuation redundancy, disturbance-aware control, thruster wake modeling, visual inspection.  \nI. INTRODUCTION  \nUNDERWATER robots have become indispensable for  \ninfrastructure inspection, environmental monitoring, and scientific exploration. High-fidelity sensing of underwater structures is critical to these applications, from detecting hairline cracks in pipelines to monitoring coral bleaching and documenting archaeological sites. However, approaching a target creates a core problem: thruster actuation from the robots induces hydrodynamic disturbances that resuspend sediments [1], [2] and reduce water clarity (Fig. 1), ultimately corrupting sensor data at the source [3] . This actuation-toperception coupling—wherein a robot’s thrusters degrade the data quality its sensors are trying to acquire—represents amechatronic bottleneck that cannot be resolved through postprocessing or algorithmic compensation alone.  \nStandard thruster configurations compound this problem. A conventional six-thruster underwater vehicle provides exactly six control inputs for six degrees of freedom—sufficient for  \nThis work was supported by the Hong Kong University of Science and Technology (Guangzhou) .  \n1All authors are with the Smart Manufacturing Thrust, Systems Hub, The Hong Kong University of Science and Technology (Guangzhou), Guangzhou, [China.](China. yicai@hkust-gz.edu.cn)[ yicai@hkust-gz.edu.cn](China. yicai@hkust-gz.edu.cn)  \nDigital Object Identifier (DOI): see top of this page.  \nFig. 1. Thruster-induced disturbance comparison. (a) Conventional ROV with sediment resuspension. (b) The ideal method maintains clear visibility.  \nmotion control but with no redundancy for secondary objectives such as environmental disturbance minimization. Trajectory tracking and environmental disturbance thus become physically coupled: satisfying one constraint necessarily dictates the other. Reducing disturbance typically requires slower, gentler motions [4], creating an apparent tradeoff between task efficiency and data quality. Without actuation redundancy, controllers cannot decouple these competing objectives.  \nCurrent motion controllers exemplify the first challenge: they optimize for vehicle-centric objectives while disregarding their environmental consequences. Trajectory tracking controllers minimize position error [5]; dynamic positioning syst","cbCaigPkDsRUz5eA","https://ap.wps.com/l/cbCaigPkDsRUz5eA","pdf",31013194,1,11,"English","en",105,"# I. Introduction\n## Actuation-to-perception coupling and hydrodynamic disturbance\n## Limitations of conventional motion controllers\n## Existing disturbance mitigation strategies and their constraints\n# Proposed approach overview","[{\"question\":\"What problem does the paper address for underwater robots near delicate targets?\",\"answer\":\"Thruster actuation can resuspend sediments and create turbulence, reducing water clarity and corrupting sensor data at the moment of acquisition.\"},{\"question\":\"How does actuation redundancy help with disturbance-aware control?\",\"answer\":\"In an over-actuated platform, multiple thrust allocations yield identical vehicle motion, allowing the controller to search the null space to minimize predicted disturbance while enforcing motion constraints.\"},{\"question\":\"What key model enables real-time redundancy resolution in the proposed method?\",\"answer\":\"The method uses a control-oriented thruster-wake proxy based on actuator-disk theory with directional attenuation, validated experimentally with 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problem does the paper address for underwater robots near delicate targets?","Question",{"text":75,"@type":76},"Thruster actuation can resuspend sediments and create turbulence, reducing water clarity and corrupting sensor data at the moment of acquisition.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How does actuation redundancy help with disturbance-aware control?",{"text":80,"@type":76},"In an over-actuated platform, multiple thrust allocations yield identical vehicle motion, allowing the controller to search the null space to minimize predicted disturbance while enforcing motion constraints.",{"name":82,"@type":73,"acceptedAnswer":83},"What key model enables real-time redundancy resolution in the proposed method?",{"text":84,"@type":76},"The method uses a control-oriented thruster-wake proxy based on actuator-disk theory with directional attenuation, validated experimentally with 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