CRUSER's TechCon

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CRUSER's TechCon

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Making Risk-Informed System Architecture Decisions in Early Autonomous System Design
(2018-04-17) Van Bossuyt, Douglas
There is a need for rapid design, manufacture, and deployment of autonomous systems for use in dangerous and evolving environments. DoD and its contractors are coming under increased pressure to field new or redesigned autonomous systems that are under budget and on schedule while being held to the expectation of systems needing to be reliable, robust, resilient safe, and survivable. A gap exists in conceptual system modeling methods to adequately, realistically, and cost-effectively model autonomous systems that can be used for early system architecture decisions. This talk presents ongoing efforts in: 1) providing functional modeling methods with refined function failure analysis tools that predict failure pathways, consequences, and likelihoods; 2) developing a tool that determines sustainability of functional models based on manufacturing processes, and with ongoing work in connecting functional models with manufacturing process selection for system components; 3) analyzing autonomous system designs for vulnerability to irrational behaviors of other systems within a system of systems; 4) making prognostics and health management system architecture decisions based upon early design modeling and simulations; and 5) analyzing autonomous and paired crewed/autonomous system mission goals using manufacturing and design knowledge, risk information, and risk attitudes of operators through a functional modeling approach. The goal of this research is to provide a toolbox of systems modeling and analysis methods for practitioners to make risk and failure-informed system architecture decisions rapidly and accurately, and develop system models in the earliest stage of design that require less redesign and result in quicker time to market, safer products, and more value to the customer.
Quantifying the benefits of manned-unmanned teaming in naval operations via data farming
(2018-04-18) Sanchez, Susan
Extensive experimentation is needed to identify and assess the capabilities and tactics that will provide the most value in developing and integrating unmanned systems into the Navy. This presentation highlights recent research by three NPS officer-students (Solem 2016, Tanalega 2018, Tilus 2018) who use different simulation modeling platforms to investigate manned-unmanned teaming for naval operations. Solem (2016) uses Map Aware Non-uniform Automata (MANA), a stable agent-based modeling platform developed for defense applications by New Zealand. Tanalega (2018) and Tilus (2018) use Orchestrated Simulation Through Modeling (OSM), together with the Littoral Combat Ship Integrated Toolkit for Mission Engineering Using Simulation (LITMUS). NSWC Dahlgren is the lead developer for OSM and LITMUS, teaming with the NPS SEED Center for software development and testing. Solem and Tilus explore combinations of a manned P-8 Poseidon aircraft and an unmanned Medium Displacement Unmanned Surface Vessel (MDUSV) in an antisubmarine warfare (ASW) scenario. Specifically, they investigate the performance of each platform operating separately followed by an examination of manned-unmanned teaming for the P-8 and MDUSV. Through parallel computation and efficient design of experiments, they simulate tens of thousands of ASW missions and vary multiple red and blue employment approaches and capabilities. The OSM/LITMUS results show that MDUSV operating alone has the lowest probability of killing the red submarine. The P-8 operating alone and the P-8 teamed with the MDUSV have nearly perfect performance in terms of red kills, although the latter reduces the conditional mean time to kill by roughly 10%. Comparison between the LITMUS studies and the earlier MANA study reveal that the OSM/LITMUS results are overly optimistic. Further improvement in the modeling platform is needed -- including the provision of a capability for representing the localization phase between the P-8's initial detection and the subsequent time and additional sonobuoys required to locate, track, and target the threat. Nonetheless, the preliminary results show substantive benefits of manned-unmanned teaming. In related work, Tanalega (2018) examines the use of MDUSVs equipped with different capability packages and tactics in a surface warfare scenario. His data farming investigation varies sensor ranges, force dispersions, formations, and emissions control policies. The results show that the addition of MDUSV to a surface force can triple the chance that it is the first to fire. The research also provides guidance about desirable sensor characteristics and MDUSV tactics. References Solem, K. (2016). Quantifying the potential benefits of antisubmarine warfare (ASW) continuous trail unmanned vessels (ACTUV) in a tactical ASW Scenario (Master's thesis). Naval Postgraduate School, Monterey, CA. Tanalega, J. (2018). Analyzing unmanned surface tactics with the Lightweight Interstitials Toolbox for Mission Engineering using Simulation (Master's thesis). Naval Postgraduate School, Monterey, CA. Tilus, P. (2018). Assessing Orchestrated Simulation Through Modeling to quantify the benefits of unmanned-manned teaming in a tactical ASW scenario (Master's thesis). Naval Postgraduate School, Monterey, CA.
CRUSER TechCon 2018 Roster of speakers, Tuesday 3: Operations
(2018-04-18)
MEMS acoustic directional finder for small flying UAS [video]
(2018-04-18) Alves, Fabio; Karunasiri, Gamani; Physics (PH)
When compared with the electromagnetic counterparts, acoustic sensors have many advantages that include non-line-of-sight, passive, low-cost, and low power, weight, and size. Acoustic sensors are the primary sensors employed in most unattended ground sensor systems because they can provide detection, direction finding, classification, tracking, and accurate cueing of other high-resolution sensors. The ability to detect and localize aerial UAS with acoustic sensors is not straightforward and require a sensor that can filter out intense background noise and spectral bands not related to the intrinsic acoustic signature of the source. In addition, highly accurate directionality is required. Our team is developing bio-inspired acoustic MEMS sensors to perform this specific task. In order to accomplish that it is necessary to understand the acoustic signature of the target. Typically, the acoustic spectrum of a quadcopter in hovering regime is dominated by high and sustained tone noise at the blade passing frequency and shaft rate and their harmonics up to the mid frequency range of hearing. Broadband noise in the spectra become dominant in the mid and high frequency ranges indicating that rotor self-noise could be significant part of the system noise. Variations in the acoustic spectra of different rotor-sets at the same thrust are significant around the mid and high frequencies at which the broadband component dominates. However between 600 and 1300 Hz some spectral features seem to be perennial (independent of flight regime, payload, etc.). In a realistic operational environment, topography, landmarks, obstacles, weather and different fight regimes influences must be added to the intrinsic signature. In this context, the 18th JIFX was instrumental to provide a variety of environmental and topographical conditions as well as different platforms to be analyzed. Acoustic signatures of 8 different UAS were recorded so far and preliminary observation of the data show that indeed very strong narrow spectral features were located between 600 and 1300 Hz, as shown in Figure 1, for a Yuneec Typhoon 600 Hexacopter. These spectral characteristics will be used as design requirements for the MEMS sensor, whose resonant response is ideal for increasing the sensitivity (10 to 1000 times better than convectional microphones) and naturally filter out the undesirable acoustic spectral bands for enhancing the detection capabilities.
Autonomous Wave Glider based Environmental Sampling in Support of Electromagnetic Maneuver Warfare
(2018-04-18) Wang, Qing; Yamaguchi, Ryan; Meteorology
Improved capability to model and forecast atmospheric effects on electromagnetic (EM) spectrum propagation in the battle-space has broad application throughout Navy and Department of Defense functional areas. Many Naval systems utilize the EM energy, active or passive, for applications in remote sensing (radar), communications (radio), and optical (high energy laser) systems. Refraction is an atmospheric property that bends EM energy from a straight-line path and is caused by spatial variations in temperature, humidity, and pressure. Meanwhile, small perturbations of the refraction index significantly impact free-space optical and high energy laser (HEL) weapon performance. These effects need to be quantified and predicted for all weather conditions. The Liquid Robotics Wave Glider, known as the Sensor Hosting Autonomous Remote Craft (SHARC) for Navy applications, is a slow-moving platform that can be deployed for extended missions. With adequate sensors onboard SHARC, environmental data can be collected in data sparse regions or hazardous environments. The standard SHARC is instrumented with a default meteorological station (Airmar PB200) that samples air pressure, temperature, wind speed and wind direction at 1.12 m above the water surface. The SHARC automatically transmits 10-minute averaged data through an Iridium satellite link. To maximize SHARC utilization in future Navy-relevant applications, NPS Meteorology Department partnered with the NPS Physics Department and engaged in integration and testing efforts to evaluate the default Airmar PB200 and sought optimal sensors for air-sea interaction and EM propagation studies. In this effort, we developed two SHARC payloads, the 'NPS Met� and �NPS Turbulence� systems. NPS Met payload measures pressure, air temperature, wind, SST, and relative humidity. This SHARC payload package was deployed three times in the Monterey Bay, along with a collocated drifting buoy (Marine Air-Sea Flux buoy, or MASFlux) with proven flux, mean, wave, and SST measurement for comparison and validation. NPS Met was augmented with a 3-D ultrasonic wind anemometer sensor and became the NPS Turbulence payload. Addition of the 20-Hz turbulence sampling required considerable modifications to the data acquisition and power management components. The NPS-owned Liquid Robotics WaveGlider SV2 (previously Mako, now named Thresher) was deployed with the turbulence payload during the Coupled Air-Sea Processes and EM ducting Research east coast field campaign (CASPER-East). Data collected from Thresher in CASPER-East were limited due to water ingress and salt corrosion inside the meteorological sensors and data acquisition system. The sensor payload configuration for Thresher was redesigned for the CASPER west coast field campaign (CASPER-West) to ensure continuous data collection during its deployment, while maintaining minimal flow distortions. In this presentation, we will showcase the Thresher payload design iterations, present example results from the met and turbulence payloads, and relate those results to the environmental impact on Navy operations using EM spectrum for sensing, communication, and weapon systems.
2013_04 TechCon: CRUSER Technical Continuum
(Monterey, California: Naval Postgraduate School, 2013-04) Consortium for Robotics and Unmanned Systems Education and Research (CRUSER); Naval Postgraduate School (U.S.)
September 2019 WIC Workshop Quick Look Report
(2019-04-17)
Warfare Innovation Continuum (WIC) Workshop: Logistics in Contested Environments
The Effect of Perceived Benevolence on Trust in Automation
(2018-04-18) Clark, Tiffany
As autonomy becomes more ubiquitous, human-machine teams are becoming more common and may very well be a staple of future military and civilian operations. In many ways, human-machine teaming will look much like human-human teaming, while in some ways it will look very different. One vital aspect of teaming that includes both similarities and differences as mentioned is trust, and a person�s reliance on teammates�whether human or autonomous machine�based on that level of trust. Inter-human trust on teams is typically damaged through actions that fall into one of two broad categories: a competency-based error, where someone breaches trust due to lack of knowledge or miscalculation; or an integrity-based violation, where someone purposefully chooses to breach trust in order to gain some other objective. Although human-automation trust with regard to competency-based errors has been studied, searches turn up little in the way of trust research with automation committing integrity-based violations. Until recently, the assumption that automation was not capable of integrity-based violations seemed obvious and sound. Yet with progressing developments in artificial intelligence and ever-increasing skillsets of cyber hackers, that assumption may need a second look. If one accepts that automation of the future may be capable of purposefully breaching trust (or that cyber hackers will be capable of creating the same effect), the trust response of humans in receipt of such a breach should be studied. Using reliance measures as an indicator of trust, this research attempts to map the time-response of human trust in automation after experiencing a competency-based error versus an integrity-based violation on the part of the automation.
TECHCON 2017 - Schedule
(Monterey, California. Naval Postgraduate School, 2017-04) Consortium for Robotics and Unmanned Systems Education and Research (CRUSER)
September 2023 WIC Workshop Quick Look Report
(2023-09)
This rapid concept generation workshop was held 18-21 September 2023 and included 108 active participants, with just over 80 on the NPS campus in Monterey and the rest on the NPS “Virtual Campus” via ZoomGov.