Clandestine Mine Countermeasures Optimization for Autonomy and Risk Assessment

NPS NRP Executive SummaryThe PRC and Russia are the greatest miners in the world and are prepared to employ mines to tilt the Great Power Competition (GPC) in their favor. Mines are inexpensive, easily deployed, and put Distributed Maritime Operations (DMO) at high-risk. Countering mines within acceptable risk levels and mission timelines is required to support DMO operational requirements. Although the development and integration of autonomous vehicles should improve DMO, research and development of new tools for optimizing distributed search effort are required to minimize risk to the force. These tools must consider the constraints placed on mine countermeasures (MCM) by the challenges of GPC. Today's MCM systems, for example, rely on surface and airborne assets, with associated force protection burdens required to establish and maintain a permissive environment. In the future, naval forces must be prepared to operate in contested environments where overt operations are denied and supporting technologies (GPS, communications, etc.) are severely limited. Autonomous underwater vehicles (AUVs) have potential to conduct clandestine MCM operations, but new approaches for conducting collaborative search with multiple AUVs are needed to fully realize their potential. Research is required to identify and assess new methods for conducting entirely clandestine MCM.N8 - Integration of Capabilities & ResourcesThis research is supported by funding from the Naval Postgraduate School, Naval Research Program (PE 0605853N/2098). https://nps.edu/nrpChief of Naval Operations (CNO)Approved for public release. Distribution is unlimited.

Clandestine Mine Countermeasures Optimization for Autonomy and Risk Assessment

NPS NRP Technical ReportThe PRC and Russia are the greatest miners in the world and are prepared to employ mines to tilt the Great Power Competition (GPC) in their favor. Mines are inexpensive, easily deployed, and put Distributed Maritime Operations (DMO) at high-risk. Countering mines within acceptable risk levels and mission timelines is required to support DMO operational requirements. Although the development and integration of autonomous vehicles should improve DMO, research and development of new tools for optimizing distributed search effort are required to minimize risk to the force. These tools must consider the constraints placed on mine countermeasures (MCM) by the challenges of GPC. Today's MCM systems, for example, rely on surface and airborne assets, with associated force protection burdens required to establish and maintain a permissive environment. In the future, naval forces must be prepared to operate in contested environments where overt operations are denied and supporting technologies (GPS, communications, etc.) are severely limited. Autonomous underwater vehicles (AUVs) have potential to conduct clandestine MCM operations, but new approaches for conducting collaborative search with multiple AUVs are needed to fully realize their potential. Research is required to identify and assess new methods for conducting entirely clandestine MCM.N8 - Integration of Capabilities & ResourcesThis research is supported by funding from the Naval Postgraduate School, Naval Research Program (PE 0605853N/2098). https://nps.edu/nrpChief of Naval Operations (CNO)Approved for public release. Distribution is unlimited.

Performance Impacts on Unmanned Vehicle and Sensor Capabilities for Standoff Mine Detection in the Very Shallow Water, Surf Zone, and Beach Zone

NPS NRP Executive SummaryThe Very Shallow Water, Surf Zone, and Beach Zone (VSW/SZ/BZ) environments present extreme challenges for the safe standoff detection of objects, such as mines, explosive ordnance, or natural obstacles such as rocks and shoals. Wave action adversely impacts the performance of conventional unmanned underwater vehicles (UUVs) and remotely operated vehicles (ROVs) that employ sonar or optical imaging sensors. Unmanned aerial vehicles (UAVs) or bottom crawling vehicles that use different sensing modalities may be more effective in these environments. Research is needed to quantify the limitations of current standoff detection sensors deployed from mine countermeasures (MCM) vehicles and recommend promising alternatives for future technology development. This study has two main research objectives. First, we will work with project sponsors and subject matter experts to identify and compare the current state of various technologies for standoff detection of explosive ordnance in the VSW/SZ/BZ. Second, we will leverage NPS experimental capabilities to assess the performance impacts on different MCM vehicles and sensors subjected to wave disturbances in VSW/SZ environments. Specifically, we will conduct semi-captive tests of different MCM vehicle types in a tow tank with wave making capability to simulate VSW/SZ conditions. The measured wave-induced motion profiles will be used to analyze the effects of platform motion on the detection performance of conventional imaging sensors using standard object detection algorithms. Understanding the capabilities of existing technologies, and how they can be expected to perform in these challenging domains, will help inform programs of record and guide future technology investment by the US Navy and US Marine Corps. Research Project ID NPS-21-J212 combines two Topic/Research Projects: NPS-21-M212 and elements of NPS-21-N271.Marine Corps Forces Command (COMMARFORCOM)Navy Expeditionary Combat CommandThis research is supported by funding from the Naval Postgraduate School, Naval Research Program (PE 0605853N/2098). https://nps.edu/nrpChief of Naval Operations (CNO)Approved for public release. Distribution is unlimited.

Performance Impacts on Unmanned Vehicle and Sensor Capabilities for Standoff Mine Detection in the Very Shallow Water, Surf Zone, and Beach Zone

NPS NRP Project PosterThe Very Shallow Water, Surf Zone, and Beach Zone (VSW/SZ/BZ) environments present extreme challenges for the safe standoff detection of objects, such as mines, explosive ordnance, or natural obstacles such as rocks and shoals. Wave action adversely impacts the performance of conventional unmanned underwater vehicles (UUVs) and remotely operated vehicles (ROVs) that employ sonar or optical imaging sensors. Unmanned aerial vehicles (UAVs) or bottom crawling vehicles that use different sensing modalities may be more effective in these environments. Research is needed to quantify the limitations of current standoff detection sensors deployed from mine countermeasures (MCM) vehicles and recommend promising alternatives for future technology development. This study has two main research objectives. First, we will work with project sponsors and subject matter experts to identify and compare the current state of various technologies for standoff detection of explosive ordnance in the VSW/SZ/BZ. Second, we will leverage NPS experimental capabilities to assess the performance impacts on different MCM vehicles and sensors subjected to wave disturbances in VSW/SZ environments. Specifically, we will conduct semi-captive tests of different MCM vehicle types in a tow tank with wave making capability to simulate VSW/SZ conditions. The measured wave-induced motion profiles will be used to analyze the effects of platform motion on the detection performance of conventional imaging sensors using standard object detection algorithms. Understanding the capabilities of existing technologies, and how they can be expected to perform in these challenging domains, will help inform programs of record and guide future technology investment by the US Navy and US Marine Corps. Research Project ID NPS-21-J212 combines two Topic/Research Projects: NPS-21-M212 and elements of NPS-21-N271.Marine Corps Forces Command (COMMARFORCOM)Navy Expeditionary Combat CommandThis research is supported by funding from the Naval Postgraduate School, Naval Research Program (PE 0605853N/2098). https://nps.edu/nrpChief of Naval Operations (CNO)Approved for public release. Distribution is unlimited.

Optimal sensor-based motion planning for autonomous vehicle teams

Reissued 30 May 2017 with correction to student's affiliation on title page.Autonomous vehicle teams have great potential in a wide range of maritime sensing applications, including mine countermeasures (MCM). A key enabler for successfully employing autonomous vehicles in MCM missions is motion planning, a collection of algo-rithms for designing trajectories that vehicles must follow. For maximum utility, these algorithms must consider the capabilities and limitations of each team member. At a minimum, they should incorporate dynamic and operational constraints to ensure trajectories are feasible. Another goal is maximizing sensor performance in the presence of uncertainty. Optimal control provides a useful frame-work for solving these types of motion planning problems with dynamic constraints and di_x000B_erent performance objectives, but they usually require numerical solutions. Recent advances in numerical methods have produced a general mathematical and computational framework for numerically solving optimal control problems with parameter uncertainty—generalized optimal control (GenOC)— thus making it possible to numerically solve optimal search problems with multiple searcher, sensor, and target models. In this dissertation, we use the GenOC framework to solve motion planning problems for di_x000B_erentMCMsearch missions conducted by autonomous surface and underwater vehicles. Physics-based sonar detection models are developed for operationally relevant MCM sensors, and the resulting optimal search trajectories improve mine detection performance over conventional lawnmower survey patterns—especially under time or resource constraints. Simulation results highlight the flexibility of this approach for optimal mo-tion planning and pre-mission analysis. Finally, a novel application of this framework is presented to address inverse problems relating search performance to sensor design, team composition, and mission planning for MCM CONOPS development.http://archive.org/details/optimalsensorbas1094553003Approved for public release; distribution is unlimited

CRUSER Tech Talks: Optimal Motion Planning for Mine Countermeasures

CRUSER Tech Talk

AUV Control and Communication using Underwater Acoustic Networks

Underwater acoustic networks can be quite effective to establish communication links between autonomous underwater vehicles (AUVs) and other vehicles or control units, enabling complex vehicle applications and control scenarios. A communications and control framework to support the use of underwater acoustic networks and sample application scenarios are described for single and multi-AUV operation