Please check back often for the latest award announcements, events, and corporate happenings at IAI...
April 2013: Navy awards IAI a follow-on contract to develop a Cognitive Ultra-Low Power Sensor System (CUPSS).
The Navy’s role in the Global War on Terrorism (GWOT) requires reliable long-term intelligence, reconnaissance, and surveillance. For long time frame scenarios, the main challenge faced by methods of automated surveillance and threat identification is the significant power resources required by sensor systems. Developing power efficient, low cost, long term, smart sensing technologies will be very useful to address this challenge. IAI, in collaboration with University of Michigan, is developing a novel sensing system called Cognitive Ultra-low Power Sensor System (CUPSS). CUPPS is a multimodal sensing node with wireless fencing capability supported by ultra low power (pW-nW), and a compact Phoenix hardware platform that leverages a comprehensive sleep strategy using a unique power gating approach, a CPU with compact instruction set, a custom low leakage memory cell, adaptive leakage management in the data memory, and data memory compression. In addition, CUPSS has a cognitive sensor management framework for heterogeneous, sensor modalities; sensed events; and signal propagation that allows for smart sensor positioning and power management. It features hierarchical sensor placement and fusion architecture to efficiently reduce model complexity and uncertainty and to identify friendly encounters from threat intrusions. Finally, it has a sensor middleware supporting hardware and algorithm abstraction and software wizards to rapidly integrate new sensors, and easily update the sensor sleep/trigger hierarchy and rules by a non-technical human operator. A CUPSS architecture will be built and demonstrated for a wide variety of sensing modalities, including radio and vision-based sensors, seismic and acoustic sensors suitable for advanced laboratory and supervised field-testing.
April 2013: Navy awards IAI a new contract to develop a Highly Scalable and Autonomous NetOps Analytics System for Navy Tactical Networks.
The current naval networking environment is primarily composed of several enterprise computing and communications environments, which can be characterized as large scale heterogeneous network environments. Due to the inherited complex nature of the network, it is quite challenging to provide a synchronized view of data, and perform autonomous analytics from the large volume of geographically dispersed data. IAI has been awarded a new contract entitled “Highly Scalable and Autonomous NetOps Analytics (SANA) System for Navy Tactical Networks.” While there are currently many network situational awareness tools available, the objective of this program is to develop superior and secure situational awareness and user efficiency that would benefit any large network operating in a cloud environment. IAI proposes to develop a highly scalable and autonomous NetOps Analytics (SANA) system, which defines and captures abnormalities in information and network behaviors to generate alerts if any abnormalities are detected. In addition, the proposed system maps missions to required resources and guarantees synchronized information sharing to increase level of information value, health and trust. SANA can be extended to a broad range of large commercial network operations to deal with issues of network performance, operational availability, and security.
March 2013: Army awards IAI a follow-on contract to develop a Radio Frequency Network Emulation Tool for evaluating Wireless Mesh Networks.
Current wireless communication hardware is optimized to receive signals from a single user. IAI has developed new technology to allow simultaneous reception and decoding of signals from multiple sources, thus increasing spectral efficiency in analog and digital signal transmission. Further development of this technology requires rigorous testing in a networked environment, including performance evaluation of protocols at different layers and the behavior of physical layer hardware. Evaluating protocols or solutions for wireless networks is difficult, as simulation is inadequate, and wireless field tests are costly, slow, and not easily scalable, controllable, or repeatable. IAI has been awarded a contract entitled, “Preservation of Information from Non-Collaborative Sources (PINSs),” to develop a network emulation tool that can test and evaluate its new technology. A next generation radio frequency network channel emulator simulator tool called RFnest-48 will be developed. It can evaluate a fully connected wireless mesh network consisting of up to 48 nodes, called ‘real’ nodes, represented using physical devices; and 200 nodes called ‘virtual’ nodes, simulated in software. Virtual and real nodes interact seamlessly through devices called ‘surrogate’ nodes that represent the interference on virtual nodes due to real nodes, and vice-versa. RFnest-48 supports devices with bandwidths up to 150 MHz, and models a multipath fading propagation channel with a flexible number of resolvable components. Additionally, RFnest-48 has multiple-antenna capabilities to support at least 12 RF devices with up to 4 antennas for each node. RFnest-48 combines direct digital conversion and an RF front-end design to support incoming frequencies between DC and 3 GHz. RFnest-48 will improve the design, development and evaluation of dynamic wireless networks. Applications include realistic protocol evaluation, large-scale evaluation, replaying field tests, and model validation.
March 2013: Air Force awards IAI a new contract to develop a Robust Decision Tool for Persistent Space Self Defense Systems.
The increasing demands of space superiority require a space self defense system with space situation awareness (SSA), or understanding of dynamic events with space assets. Such a system requires sensors to determine the position and velocity of space objects, predict orbits, detect adversary behavior and prevent attacks. IAI and its collaborator, University of New Orleans, propose to apply an advanced game theoretic approach to design a robust, decision-making tool for space self defense systems. A realistic cyber-physical system model will be developed. Then, a dynamic and distributed sensor management algorithm will be developed via a game theoretic approach for maneuver detection and persistent multi-object tracking. Advanced estimation and tracking techniques will be designed by applying nonlinear filters. Finally, a pursuit-evasion game will be designed among all observers and targets to represent their interactions in terms of orbit maneuver behavior and the resulting collision alert for decision support. This approach uses innovative game models to track space objects, analyze their orbits, and provide decision tools for space surveillance systems with self-defense capabilities. It incorporates threat modeling and analysis based on the pursuit-evasion game based active learning of deceptive behavior, nonlinear filters, cooperative sensing for persistent space object tracking by using comprehensive and realistic models of space platforms and service oriented architectures. The proposed framework will be tested via IAI’s wireless network emulation platform RFnestTM with respect to heterogeneous tracking objectives including accuracy, delay, and communication overhead. Supported by the repeatable and scalable experimentation capability of RFnestTM, this approach will facilitate advanced prototyping of effective decision making tools for persistent space self defense systems.
March 2013: OSD/Air Force awards IAI a new contract to develop LASER: A Linguistic enriched And Scalable Event attribute extRaction System.
The fast growth of web data and HUMINT reports has resulted in intelligence analysts having to rapidly monitor and analyze event information from massive amounts of unstructured textual data, in order to achieve and maintain persistent Situational Awareness (SA). A tool to automatically extract accurate events while distinguishing between real and hypothetical events, true and false events, frequently occurring and specific events, and past, ongoing and future events, will be useful. IAI proposes to develop an innovative Linguistic enriched And Scalable Event attribute extRaction System: LASER, to address this issue. LASER’s first innovation is that it integrates a rich set of specialized linguistic features exploited from lexical, syntactic and semantic levels into each of the four classification models for the event attributes of modality, polarity, genericity and tense. Secondly, it adopts robust classification models that can handle the unbalanced class problem in event attribute extraction. Finally, it incorporates three post-correction approaches to bring more performance gains to event attribute extraction. LASER also leverages a state-of-the-art event tagger that ensures that the four event attributes can be extracted on top of accurately extracted events. Furthermore, LASER uses powerful cloud computing architecture for information management and algorithmic computation. LASER leverages IAI’s data mining framework, ABMiner, to enable distributed processing of the computational intensive algorithms involved in event extraction and event attribute extraction. ABMiner provides more than 400 algorithms for both supervised and unsupervised learning aggregated from IAI’s machine learning projects and open source libraries such as Weka and RapidMiner. LASER has a wide range of potential applications in the military, as well as in commercial law enforcement, Homeland Security, financial and medical markets.
February 2013: OSD/Navy awards IAI a follow-on contract to develop a Dynamic Warehousing and Mining System for Human Social Cultural Behavioral Data.
Non-kinetic, asymmetric and sustainability operations all require good data for modeling human social cultural behavior (HSCB). Text communication provides good HSCB data, but it is vast, becomes obsolete quickly, and is not warehoused or mined in ways relevant to HSCB analysis. A system that can dynamically collect unfiltered textual communication data for use in HSCB modeling and analysis would be useful. The Dynamic Warehousing and Mining (DWM) framework being developed by IAI handles in-situ HSCB data collection and analysis. It is a large-scale, dynamic approach for collecting, organizing and analyzing massive data to assess HSCB dimensions for a given group, and to predict current belief states and likely intended actions. DWM has three layers: the data collection layer, the analysis layer, and the application layer. The data collection layer includes HSCB data sources, and an agent-based data collection component that automatically extracts, transforms, and loads various types of data from large-scale data sources. The analysis layer includes a HSCB feature analysis component, a data cube engine, and a data mining and modeling engine. The application layer includes a set of integrated data/model query, and visualization services. DWM utilizes software agent technology to achieve automated, scalable collection and real-time processing of HSCB data. Multiple agents work in parallel to scale up the execution of complex analysis tasks including linguistic feature analysis, data cubing, mining and modeling. DWM leverages IAI’s Agent-Based Data Miner (ABMiner) data mining platform for HSCB modeling. ABMiner integrates hundreds of data mining algorithms from IAI’s machine learning projects and open sources libraries such as Weka and RapidMiner. DWM has standardized search and query capability and can support many HSCB applications and products.
February 2013: OSD/Air Force awards IAI a new contract to develop a Toolkit for Automated Cyber Security Assessment and Evaluation Tests.
Large datasets are created by the high-fidelity security assessments of military and commercial software systems. Managing this captured information is hard, especially when cyber tests are performed in a distributed networking environment. An automated tool to manage, process and analyze these datasets will simplify the manual work in current cyber evaluations, and increase the efficiency of the tests. To address these issues, IAI has been awarded a contract entitled, “Hermes: A Visualized and Automated Cyber Security Assessment Toolkit.” The Hermes framework and toolkit for cyber security assessment and evaluation tests facilitates managing, processing, and analyzing large logging datasets from distributed and service-centric computing test bed. Further, it gains an aggregate system view before, during, and after assessment exercises, and delivers analytical results on various performance metrics qualitatively, quantitatively, and visually. Hermes also gives predictive analysis based on network topology, attack progression, and host or application status. It provides a holistic DVR-like visualization that captures the hardware and software resources in the test bed, and the progress of attack and defense, and allows testers to record and repeatedly replay assessment exercises. The key innovations of Hermes are the distributed logging report and centralized analysis for complex cyber security assessments, the customizable real-time and post-exercise visualization of evaluation progress with aggregated insight, and the automated cyber test execution through iterative and progressive generation of test scripts. The Hermes framework will give cyber testers insights into attack and defense mechanisms and Systems Under Test (SUT). Hermes leverages IAI’s expertise in Cyber Security, Computer Networking, and Situation Awareness and will utilize IAI’s available technologies and open source software to create a powerful, flexible, and robust framework for Cyber Security assessment tests.
February 2013: Missile Defense Agency awards IAI a new contract to develop an innovative Human-In-Control Model Design for BMDS simulations.
The performance of human operators significantly shapes the capabilities of the entire BMDS. Simulations of warfighter performance can benefit from incorporating real-world variations in operator proficiency, timeliness, creativity, fatigue or morale. Modeling Human-in-Control actions will increase the credibility of such simulations, which can be used in Performance Assessment, Futuristic Concept Analyses, Ground Tests, and Training, Exercises and Wargames. To address this, IAI and its collaborator, University of Michigan, have been awarded a contract entitled “Human-In-Control (HIC) Modeling and Integration Framework for BMDS Simulations.” An innovative HIC software modeling and integration framework will be built around objectively quantified cognitive models of human operators. These include the Executive-Process/Interactive Control (EPIC) and the GOMS (Goal Operator Method and Selection rules) Language Evaluation and Analysis (GLEAN). The framework provides the ability to model existing or futuristic operator workstations, which is used as declarative knowledge to develop high & low-fidelity cognitive models. It supports operator modeling of varying proficiency by allowing users to define task-specific timeline distributions, while the decisions are driven by fixed perceptual, cognitive, motor processor parameters and constraints. The cognitive model can interact with external decision models to determine the quantitative value of the outcome of certain motor tasks, so that meaningful simulation events can be generated for other BMDS simulation elements and components. A proposed HLA framework to interface with perceptual signal and motor actions declared in the HIC model provides an integration layer and a middleware to manage simulation time, and seeds to repeatable stochastic behavior external to the HIC model. Finally, a proposed enterprise service with scenario planning capability, to configure a simulation event from a repository of operator and workstation models, will support training and BMDS Performance Assessment.
March 2013: IAI releases the MOXIEfit™ App for Android mobile devices.
MOXIEfit™, developed by Intelligent Automation, Inc. (IAI), provides a virtual personal trainer on a smartphone, to motivate and support a step-by-step achievable weight loss program. MOXIEfit’s virtual personal trainer, Mandy, provides personalized coaching during workouts to help users stay motivated and stick with their fitness program. Mandy helps the user create a weight loss program that includes a weekly workout schedule and weigh-ins. Mandy reminds the user when it is time to exercise and provides motivational feedback throughout the workout. Mandy praises the user for keeping on track with their weight loss goal and automatically adjusts the plan if the user gets off track – all without counting calories! MOXIEfit is the first smartphone application to provide a virtual personal trainer that cares about helping users get fit.
Another key feature of MOXIEfit is MOXIEmatch™, an adaptive music feedback system that matches songs from the user’s music library to the workout tempo. If there are no songs that perfectly match the tempo, MOXIEmatch increases or decreases the music speed to match the workout pace. This feature, coupled with Mandy’s personalized coaching, ensures users get the most benefits from their exercise. MOXIEfit can sync user data online using CarePass, Aetna’s personal health cloud that automatically syncs data between the user’s favorite health and wellness apps. As part of the CarePass ecosystem, MOXIEfit syncs fitness data such calories burned, distance, and steps as well as body measurements from weekly weigh-ins that can then be viewed online alongside health and wellness data such as nutrition from other apps.
“MOXIEfit takes a simple approach to losing weight,” according to Timothy Judkins, IAI’s mHealth Program Manager. “While MOXIEfit has all the capabilities you would expect in today’s fitness apps, the addition of the virtual personal trainer and features like MOXIEmatch will significantly help users adopt and follow a weight loss program.”
Beyond helping users lose weight, MOXIEfit was originally developed as part of an Army SBIR program to support physical rehabilitation. “Adherence to a rehabilitation program is critical for a successful recovery from injury for our wounded warriors. We see real potential for an application that could provide motivation during the recovery period," said Ashley Fisher, Health and Wellness Domain Coordinator, U.S. Army Telemedicine and Advanced Technology Research Center (TATRC).
MOXIEfit is available for Android mobile devices as a 30-day free trial and can be downloaded from the Google Play store to any Android mobile device. MOXIEfit also offers users a price discount if the application is purchased within 14 days. You can download the MOXIEfit App at: https://play.google.com/store/apps/details?id=com.iai.moxie.fit
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Intelligent Automation, Inc. (IAI) is a multifaceted private company that focuses on technology research and development. For over 25 years, IAI has developed cutting edge solutions to complex problems in areas that include mobile health, information technology, education and training, sensors and communication, signal processing, distributed systems, and robotics.
This work is supported, in part, by the US Army Medical Research and Materiel Command under Contract No.W81XWH-09-C-0134. The views, opinions and/or findings contained in this press release are those of the author(s) and should not be construed as an official Department of the Army position, policy or decision unless so designated by other documentation.
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February 2013: Air Force awards IAI a new contract for Standoff Coherent Optical Detection of Acoustic Signals.
Detection of clandestine tunnels and underground facilities is of continuing interest to DoD and Customs and Border Protection. Ongoing research to find functional and reliable sensing methods include seismic methods, since dynamic activity in tunnels emits mechanical energy that propagates in seismic waves. Resulting ground vibrations can be measured at offset distances and these signals can be used in sensing algorithms for detection, location, and discrimination of the activity. Current detection methods rely largely on emplaced sensors, such as geophones. Space-based or airborne surveillance can drastically improve standoff and surveillance coverage. To address this critical need, IAI and its collaborator, University of Maryland (UMD), have been awarded a new contract entitled, “Standoff Coherent Optical Detection of Acoustic Signals (SCODAS).” A vibrometry technique will be developed for long-range detection of very small vibrations induced in passive objects exposed to acoustic disturbances. SCODAS will leverage the vibrometry experience of UMD, and signal processing and hardware expertise of IAI. A powerful, eye-safe, infrared laser is aimed at the ground or an airborne target from an airborne platform or satellite. The possible vibrations of an object causes scattered or reflected light from the laser to return to the transmitter with a superimposed phase modulation. SCODAS measures the amplitude and phase change of the probe beam simultaneously, and the measured phase will directly translate into displacement of the sensed area or object. The distinctive frequency spectrum and other signal features will be exploited for both interference due to turbulence, and the target signatures of vehicles and underground activities. The standoff distance will be extended by trading resolution for SNR, and the effects of atmosphere induced phase fluctuations will be corrected and compensated for using a reference beam.
February 2013: Army awards IAI a new contract to develop a Virtual Clinical Assistant for PTSD professionals.
The significant number of veterans and active military personnel with potential Posttraumatic Stress Disorder (PTSD) makes it important to improve PTSD diagnosis and treatment. A powerful PTSD Clinical Decision Support System (CDSS) based on evidence-based treatment strategies will be useful. To address this critical need, IAI has been awarded a new contract entitled, “A Virtual PTSD Clinical Assistant with Cloud Computing and Mobile Interface: VPCA.” The key innovation of VPCA is using the Hadoop Ecosystem with scalable data storage and processing capability to enable the evidence based clinical decision support empowered by Watson-like predictive analytics across different domains for PTSD patients. VPCA consists of a set of indispensable components grouped in four sub-systems, and supported by a Hadoop storage system, a map reduce engine and standard vocabularies and terminologies of clinical PTSD. The first sub-system is for knowledge and rule authorization, and it transforms the PTSD decision guidelines used by practicing PTSD professionals, into business rules. The second sub-system is for data integration and warehousing in a distributed fashion, including as many clinical data as possible for Watson-like predictive analytics. The third sub-system is for knowledge and rule discovery that can automatically and continuously improve the reasoning potential of the proposed virtual assistant. The data mining algorithms in IAI’s ABMiner and its meta-optimization for model selection will be migrated into the Hadoop Ecosystem. The fourth sub-system is for online clinical decision support. VPCA uses cutting-edge natural language processing technology for clinical data, an open-source clinical decision support platform called OpenCDS, and scalable architecture based on cloud and distributed computation to handle big data. VPCA’s online decision support for diagnostics and treatment will help experienced PTSD clinicians, general practitioners and residents.
February 2013: Navy awards IAI a new contract to develop a Data Storage and Transition System for Mobile Ad Hoc Networks.
Implementing distributed data storage and sharing faces unique challenges in the military wireless domain. Military tactical networks have mobile nodes with different, specialized mission functions. They operate in a noisy, often-obstructed, and adversarial environment, where nodes can be easily lost. The network is often partitioned into smaller sub-networks, and the data is highly dynamic and time sensitive. Solutions must address performance, reliability, security, and resilience, and compatibility with future tactical platforms and components. To address these issues, IAI has been awarded a contract entitled, “DataGuard: A Secure, Reliable and Efficient Data Storage and Transition System for Mobile Ad Hoc Network.” DataGuard is a distributed system that integrates various coding techniques, data migration protocol and service evaluation model, to enable secure data storage and efficient data access in wireless ad hoc networks. Various coding techniques will be adopted, including erasure coding scheme, threshold crypto algorithm, and symmetric crypto primitives to protect data at rest and in transit against eavesdropping and Byzantine attacks. A data migration protocol will allow the data storage system to self-adapt to network dynamics. Additionally, the service evaluation model will allow data users to evaluate the data delivery service provided by the data storage nodes. The combination of coding schemes, data migration protocol, and service evaluation model will significantly improve data availability with distributed implementation in wireless ad hoc networks. Finally, the feasibility of the coding techniques, data migration protocol and service evaluation model will be demonstrated in a workable data storage and transmission prototype for wireless ad hoc networks.
February 2013: OSD/Army awards IAI a new contract to develop a Human Machine Interface for Control and Communication in Power Networks.
Power system operators in military and industrial networks have access to large amounts of data due to the transition from hardwired analog meters to large computerized panels. Limitations include the mentally intensive nature of translating data into actionable intelligence, and the reliance on operator experience to interpret and balance options. To address this, IAI and its collaborators from Florida State University have been awarded a new contract entitled “Human Machine Interface (HMI) for Efficient, Lithe, and Intuitive Operator-communication and Sense-making in Power Networks (HELIOS-PN).” IAI’s state-of-the-art agent-based software will be combined with expertise in advanced human factors engineering and power systems to create an innovative, adaptive agent-based Human Machine Interface (HMI) system. The modular, flexible, and scalable system will have an agent-based automation and decision support engine, visualization libraries, and front-end adaptive screens to integrate state-of-the-art automation and visualization techniques. The system assists in the complex task of providing the right representation of the right data at the right time, relieving the operator of lower levels of data aggregation and contingency analysis. Tools, visualizations and methods will be developed for improving the operators’ situational awareness, and enabling efficient decision-making, facilitating reliable and intuitive operator interaction. HELIOS-PN is based on the tenets of information visualization, and techniques that leverage the cognitive and perceptual capability of the human operator. The components of the system will be integrated using a distributed and scalable agent framework based on IAI’s Cybele Distributed Agent based platform. The interface system provides effective remote control and monitoring, both for stationary and mobile operators.
January 2013: IAI receives a new Army contract to develop Bio-Inspired Visual Navigation for Unmanned Ground Vehicles.
Unmanned Ground Vehicles (UGVs) are currently tele-operated, requiring continuous human assistance. Video streaming between the UGV and the Operator Control Unit (OCU) is challenging under degraded communications, and low-texture indoor environments. Controlling a UGV needs detection and tracking of viewpoint-invariant landmarks, a navigation system for semi-autonomous operation, and a simple user interface for operator command. In a low-texture indoor environment, landmark-based navigation is difficult due to lack of distinctive micro-features such as Shape Invariant Feature Transform (SIFT) and Speeded Up Robust Feature (SURF), which are commonly used image features in computer vision. To address these issues, IAI and its collaborator, University of Pennsylvania have been awarded a contract entitled “Bio-Inspired Visual Navigation: From Landmarks via Bearing to Controls.” The Bio-Inspired Visual Navigation System requires only a standard EO camera payload. A segmentation-based method extracts landmarks as closed contours around visually salient objects in the image, which can be detected even in the low-texture environment. View-invariant shape and topological features are used to recognize these landmarks from different viewpoints. The locations of these landmarks are transformed into visual guides for bearing-only navigation. Finally, an intuitive OCU user interface enables the operator to specify waypoints and destination on an image. Using this interface, the UGV can semi-autonomously navigate its surroundings to the required destination with minimal input from the operator even in a degraded communication environment. A robust and efficient fixation-based landmark tracking algorithm extracts the object boundary, and tracks landmarks smoothly and efficiently even with changes in scale and viewpoints during camera motion. This technology is useful in military surveillance and reconnaissance applications, in civilian search and rescue operations, and to control robots via the Internet or cell phone.
February 2013: IAI Distinguished Lecture Series: Presents a seminar by Professor Norman Wereley of the University of Maryland.
Dr. Wereley is the Minta Martin Professor of Aerospace Engineering and Department Chair at the University of Maryland. He serves as the Director, Smart Structures Laboratory and Composites Research Laboratory. His research interests are in dynamics and control of smart structures, with emphasis on active and passive vibration damping control applied to rotorcraft aerospace and automotive systems. The Department of Aerospace Engineering at The University of Maryland (UMD), ranked 8th among all U.S. Aerospace Graduate Programs by U.S. News and World Report, has a strong research program spanning rotorcraft - aerodynamics, aeroelasticity, CFD, flight mechanics and handing qualities,; hypersonic vehicles - aerodynamics and propulsion; space systems including space robotics, human factors, and small satellites; space propulsion; dynamics and control – collective systems (swarms), insect navigation and control, optimal control, and smart structures and materials applied to adaptive energy absorption systems for occupant protection systems in air and ground vehicles, robotics, and helicopter rotor control; and composite structures. First, an overview of collaborative research opportunities will be provided. There are many opportunities to collaborate with UMD faculty and students on a range of topics and levels of effort including grants, contracts, fellowships, lectures delivered by company personnel on campus, and support of the curriculum via design reviews, topics for research projects, and internships. The seminar discusses of how businesses, both large and small, can leverage existing capabilities by teaming with university research laboratories, and also realize large gains in productivity effectively and efficiently. The importance of developing a fruitful intellectual property strategy in this context is presented.
Date February 14th at 10:00am in the Main Conference Room.
January 2013: IAI sponsors Blair High School Robotics Team in FIRST Robotics Competition.
IAI is proudly sponsoring the Montgomery Blair High School robotics team again as they compete in the 2013 FIRST Robotics Competition. "The Blair Robot Project" (Team 449) will be competing in the Chesapeake Regional and Pittsburgh Regional events in an attempt to win a spot in the international FRC Championship in St. Louis, Missouri in April. For more information, see the team's website at http://robot.mbhs.edu/ or the FIRST website at http://www.usfirst.org.
