Virtual acoustics displays

The real time acoustic display capabilities are described which were developed for the Virtual Environment Workstation (VIEW) Project at NASA-Ames. The acoustic display is capable of generating localized acoustic cues in real time over headphones. An auditory symbology, a related collection of representational auditory 'objects' or 'icons', can be designed using ACE (Auditory Cue Editor), which links both discrete and continuously varying acoustic parameters with information or events in the display. During a given display scenario, the symbology can be dynamically coordinated in real time with 3-D visual objects, speech, and gestural displays. The types of displays feasible with the system range from simple warnings and alarms to the acoustic representation of multidimensional data or events

Evaluation of an acoustic detection algorithm for reactive collision avoidance in underwater applications

Thesis (S.B.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2013.Cataloged from PDF version of thesis.Includes bibliographical references (page 33).This thesis sought to evaluate a vehicle detection algorithm based on a passive acoustic sensor, intended for autonomous collision avoidance in Unmanned Underwater Vehicles. By placing a hydrophone at a safe distance from a dock, it was possible to record the acoustic signature generated by a small motor boat as it navigated towards, and then away from the sensor. The time-varying sound intensity was estimated by Root Mean Square of the sound amplitude in discrete samples. The time-derivative of the sound intensity was then used to estimate the time to arrival, or collision, of the acoustic source. The algorithm was found to provide a good estimate of the time to collision, with a small standard deviation for the projected collision time, when the acoustic source was moving at approximately constant speed, providing validation of the model at the proof-of-concept level.by Oscar Alberto Viquez Rojas.S.B

Towards responsive Sensitive Artificial Listeners

This paper describes work in the recently started project SEMAINE, which aims to build a set of Sensitive Artificial Listeners – conversational agents designed to sustain an interaction with a human user despite limited verbal skills, through robust recognition and generation of non-verbal behaviour in real-time, both when the agent is speaking and listening. We report on data collection and on the design of a system architecture in view of real-time responsiveness

Modeling & Simulation Education for the Acquisition and T&E Workforce: FY07 Deliverable Package

This report was prepared for CAPT Mike Lilienthal, PhD, CPE, and funded by ASN (RDA) CHENG and the Modeling and Simulation Coordination Office (MSCO).This technical report presents the deliverables for calendar year 2007 for the "Educating the Modeling and Simulation Workforce" project performed for the DoD Modeling and Simulation Steering Committee. It includes the results for spirals one and two. Spiral one is an analysis of the educational needs of the program manager, systems engineer, and test and evaluation workforces against a set of educational skill requirements developed by the project team. This is referred to as the 'learning matrix'. Spiral two is a set of module and course matrices, along with delivery options, that meets the educational needs indentified in spiral one. This is referred to as the 'learning architecture'. Supporting materials, such as case studies and a handbook, are included. These documents serve as the design framework for spirals three and four, to be completed in CY2008, and which involve the actual production and testing of the courses in the learning architecture and their longitudinal assessment. This report includes the creative work of a seven university consortium and a group of M&S stake-holders, together comprising over 60 personnel.ASN (RDA) CHENG and the Modeling and Simulation Coordination Office (MSCO).This report was prepared for CAPT Mike Lilienthal, PhD, CPE, and funded by ASN (RDA) CHENG and the Modeling and Simulation Coordination Office (MSCO)

Physics-based Concatenative Sound Synthesis of Photogrammetric models for Aural and Haptic Feedback in Virtual Environments

We present a novel physics-based concatenative sound synthesis (CSS) methodology for congruent interactions across physical, graphical, aural and haptic modalities in Virtual Environments. Navigation in aural and haptic corpora of annotated audio units is driven by user interactions with highly realistic photogrammetric based models in a game engine, where automated and interactive positional, physics and graphics data are supported. From a technical perspective, the current contribution expands existing CSS frameworks in avoiding mapping or mining the annotation data to real-time performance attributes, while guaranteeing degrees of novelty and variation for the same gesture

Modeling and Simulation Methodologies for Digital Twin in Industry 4.0

The concept of Industry 4.0 represents an innovative vision of what will be the factory of the future. The principles of this new paradigm are based on interoperability and data exchange between dierent industrial equipment. In this context, Cyber- Physical Systems (CPSs) cover one of the main roles in this revolution. The combination of models and the integration of real data coming from the field allows to obtain the virtual copy of the real plant, also called Digital Twin. The entire factory can be seen as a set of CPSs and the resulting system is also called Cyber-Physical Production System (CPPS). This CPPS represents the Digital Twin of the factory with which it would be possible analyze the real factory. The interoperability between the real industrial equipment and the Digital Twin allows to make predictions concerning the quality of the products. More in details, these analyses are related to the variability of production quality, prediction of the maintenance cycle, the accurate estimation of energy consumption and other extra-functional properties of the system. Several tools [2] allow to model a production line, considering dierent aspects of the factory (i.e. geometrical properties, the information flows etc.) However, these simulators do not provide natively any solution for the design integration of CPSs, making impossible to have precise analysis concerning the real factory. Furthermore, for the best of our knowledge, there are no solution regarding a clear integration of data coming from real equipment into CPS models that composes the entire production line. In this context, the goal of this thesis aims to define an unified methodology to design and simulate the Digital Twin of a plant, integrating data coming from real equipment. In detail, the presented methodologies focus mainly on: integration of heterogeneous models in production line simulators; Integration of heterogeneous models with ad-hoc simulation strategies; Multi-level simulation approach of CPS and integration of real data coming from sensors into models. All the presented contributions produce an environment that allows to perform simulation of the plant based not only on synthetic data, but also on real data coming from equipments

Envirosuite: An Environmentally-Immersive Programming Framework for Wireless Sensor Networks

Networked, embedded sensors allow for an instrumentation of the physical world at unprecedented granularities and from unimagined perspectives. The advent of a ubiquitous sensing era is evident. Yet, sensor network techniques are still far from entering mainstream adoption due to multiple unresolved research challenges, especially due to the high development cost of sensor network applications. Therefore, in this dissertation, we propose to design, implement, and evaluate an environmentally-immersive programming framework, called EnviroSuite, to reduce sensor network software development cost. The goal of our research is to create reusable sensor network development support for the community and reduce the adoption barriers for a broader category of users, ultimately leading to a transition of sensor networks from a research concept to a general-purpose technology available for use for a wide variety of research, government, industry, and everyday purposes. Current sensor network programming practice remains very cumbersome and inefficient for several reasons. First, most existing programming abstractions for sensor networks are either too low-level (thus too tedious and error-prone) or too high-level (unable to support the diversity of sensor network applications). Second, there is no clear separation between application-level programming and system-level programming. A significant concern is the lack of a general middleware library to isolate application developers from low-level details. Finally, testing sensor network systems is particularly challenging. Sensor systems interact heavily with a (non-repeatable) physical environment, making lab experiments not representative and on-site experiments very costly. This dissertation is targeted for a comprehensive solution that addresses all the above-mentioned problems. The EnviroSuite framework consists of (i) a new programming paradigm that exports environment-based abstractions, (ii) critical middleware services that support the abstractions and separate application programmers from tedious, low-level details, and (iii) testing tools geared for in-situ experimenting, debugging, and troubleshooting. First, we introduce a new programming paradigm, called environmentally-immersive programming (EIP), to capture the common characteristics of sensor network applications, the rich, distributed interactions with the physical environment. EIP refers to an object-based programming model in which individual objects represent physical elements in the external environment. It allows the programmer to think directly in terms of physical objects or events of interest. We provide language primitives for programmers to easily implement their environmental tracking and monitoring applications in EIP. A preprocessor translates such EIP code transparently into a library of support middleware services, central to which are object management algorithms, responsible for maintaining a unique mapping between physical and logical objects. The major outcome of sensor networks is observations of the instrumented environment, in other words, sensory data. Implementing an application mainly involves encoding how to generate, store, and collect such data. EIP object abstractions provide simple means for programmers to define how observations of the environment should be made via distributed coordination among multiple nodes, thus simplifying data generation. Yet, the next steps, namely, data storage and collection, remain complicated and fastidious. To isolate programmers from such concerns, we also include in the support library a set of data management services, comprising both network protocols and storage systems to allow data to be collected either in real-time or in a delay-tolerant manner. The final phase in sensor network software development life-cycle is testing, typically performed in-field, where the effects of environmental realities can be studied. However, physical events from the dynamic environment are normally asynchronous and non-repeatable. This lack of repeatability makes the last phase particularly difficult and costly. Hence, it is essential to have the capability to capture and replay sensing events, providing a basis not only for software testing, but also for realistic protocol comparison and parameter tuning. To achieve that, EnviroSuite also provides testing and debugging facilities that enable controllable and repeatable in-field experiments. Finally, to demonstrate the benefits of our framework, we build multiple representative applications upon EnviroSuite, drawn from both tracking systems such as military surveillance, and monitoring systems such as environmental acoustic monitoring. We install these applications into off-the-shelf hardware platforms and physically deploy the hardware into realistic environments. Empirical results collected from such deployments demonstrate the efficacy of EnviroSuite

Multi-level fusion of hard and soft information

Proceedings of: 17th International Conference on Information Fusion (FUSION 2014): Salamanca, Spain 7-10 July 2014.Driven by the underlying need for a yet to be developed framework for fusing heterogeneous data and information at different semantic levels coming from both sensory and human sources, we present some results of the research being conducted within the NATO Research Task Group IST-106/RTG-051 on "Information Filtering and Multi Source Information Fusion". As part of this on-going effort, we discuss here a first outcome of our investigation on multi-level fusion. It deals with removing the first hurdle between data/information sources and processes being at different levels: representation. Our contention here is that a common representation and description framework is the premise for enabling processing overarching different semantic levels. To this end we discuss here the use of the Battle Management Language (BML) as a way ("lingua franca") to encode sensory data, a priori and contextual knowledge, both as hard and soft data.Publicad