iDISPLA
 
 

THE ASPIRE AND CCI PROJECTS

The ARMY STRATEGIC PROGRAM FOR INNOVATION, RESEARCH & EMPLOYMENT (ASPIRE)
COMMONWEALTH CYBER INITIATIVE
  1. Deep Learning Language Models for Military Infrared Image Captioning and Understanding:
    Recent advances in Deep Learning Language Models have revolutionized image captioning and image understanding in the commercial world. However, there is not necessarily and automatic transfer of these techniques to infrared images of interest to C5ISR. This project would leverage and enhance commercial Language Models for infrared environments.
    University: CCNY
  2. Deep Learning Language Models for Military Infrared Image Captioning and Understanding:
    Recent advances in Deep Learning Language Models have revolutionized image captioning and image understanding in the commercial world. However, there is not necessarily and automatic transfer of these techniques to infrared images of interest to C5ISR. This project would leverage and enhance commercial Language Models for infrared environments.
    University: VCU
  3. Sensor Testing:
    Design and build a platform on which various sensors can be mounted for controlled solar exposure for solar damage assessment. This could take the form of a solar tracking platform for use outdoors or a self-contained solar simulator capable of projecting an image of a simulated sun. If the former, the platform should be capable of tracking the sun automatically (2 axis preferred) and taking a manually-input slew program. A rapid but variable slew rate is desired. If the latter, the source size as projected on the sensor as well as the spectral power across at least the midwave and longwave bands (5-14 micrometer) and preferably visible to longwave bands (0.4-14 micrometer) should be accurate. An ability to slew either the source or detector along at least one axis is desirable. In both cases, a controllable shutter should be included. The mounting platform should utilize one-fourth-20 tapped holes on 1 inch or half inch centers and be capable of supporting a load of at least 2.5 kg, preferably greater or equal to 5 kg. Platform should include control software which can be modified and updated by the end user as needed.
    University: CCNY
  4. Aided Target Recognition, Image Processing:
    Image processing methods for detecting and classifying objects of interest in Electro-Optical and Infrared (EO/IR) imagery is a valuable technology supporting automation in many applications including military sensing. Deep Convolutional Neural Networks (CNNs) and Vision Transformers (ViTs) are machine learning algorithms that are currently the state-of-the-art for detecting and classifying resolved objects. These algorithms are trained and evaluated on labeled data sets and performance depends on many factors, including intra-class variance, inter-class variance and pre-processing methods. The US Army C5ISR RTI Directorate is interested in studying the impact of class selection methods and intra-class variance on overall algorithm performance. Typically, classes are selected based on an existing ontology, functional differences between objects or subjective assessment of discriminating object features. This project will involve a literature review on the subject, selection of appropriate publicly-available data sets and classification algorithms, and conducting.
    University: CCNY
  5. Multivalent Metal-Ion Rechargeable Batteries:
    Multivalent metal-ion batteries show promise as the next generation of rechargeable batteries past lithium-ion, boasting improved energy density (by weight and by volume), affordability, safety, and domestic sourcing of raw materials, all of which are important to the Army's energy storage needs. However, there still exist technical challenges to implementing multivalent metal- ion technologies to meet real world demands. Technical challenges that must be addressed include the development of compatible electrolytes, formation of robust solid electrolyte interface (SEI) layers, design of cathode materials that allow rapid multivalent ion adsorption and release, ability to operate at low temperatures, and manufacturability at large scale. This topic aims to address these challenges to assess the feasibility of multivalent metal-ion batteries in Army applications.
    University: NCAT
  6. Solid State Lithium Metal Batteries:
    Rechargeable batteries that utilize solid state electrolyte and lithium metal technologies can provide increased energy density with improved safety and stability for future Army applications. Challenges to implementation of these technologies, such as improved conductivity and ion transport of the electrolyte, improved charge transfer at interfaces, reduced dendrite formation, etc. must be overcome to ensure practical application. This topic aims to address these challenges to make battery advancements that meet requirements of Army applications.
    University: NCAT
  7. Software Defined Radios for communications (4G/5G/WIFI) and Spectrum Situational Awareness:
    Investigate software defined radios and applications for communications systems (such as but not limited to 4G/5G/wifi) which may also be re-tasked on command to perform spectrum situational awareness and analysis tasks. The device(s) under investigation should demonstrate the ability to transfer and receive communications (data, video, voice) and then quickly with little operator configuration items be re-tasked to conduct spectrum analysis tasks. Spectrum analysis tasks would include radio frequency measurements in and outside the operating range of the communications systems in use, power/amplitude response, and advanced signals and spectrum analysis. Consideration should be given to easy to use operator interfaces to configure and operate the software defined radio for these purposes.
    University: VCU
  8. Computer Vision / Object-Detection:
    The fields of computer vision and object detection are evolving rapidly, and AIP Branch is invested in identifying and applying state-of-the-art detection model concepts from sources such as academia. This proposal seeks to identify one or more promising new methods, apply them to real data, and quantitatively assess their performance against a test data set. Countermine / AIP currently has a new unclassified RGB dataset that consists of various vehicles and people cleaned and amassed from several public datasets. AIP would like to task ASPIRE participants with developing real-time object-detection models to examine novel model architectures to be leveraged for internal algorithm development. AIP will also be initiating an approval process for an additional dataset that was collected from long-wave infrared (LWIR) sensors on various vehicles and people. If this data is formally approved for release when the program begins, all participants will need to be U.S. citizens in order to support this work. The participants involved for this project should focus research and development in small object- detection modelling. The field of small object-detection is under researched and could give way to publishable material. AIP will work with participants and stand-up bi-monthly meetings to discuss updates and deliverables. A baseline model for the RGB dataset will be delivered by the students 2 months from the program start date with an expected minimum mAP@0.5 of approximately 0.5. AIP will expect additional fine-tuned models at the program's conclusion.
    University: VT
  9. Solar-Power Assisted UAVs:
    The use of unmanned aerial systems by the military has grown significantly in recent years along with the scope of operation. These systems are required to stay aloft for long periods of time while powering sensors, multiple communications systems and additional reconnaissance equipment. The ability to design efficient solar powered UAV power systems for charging during operation is key to meeting operational objectives. The goal of this project is to design, build and demonstrate.
    University: CNU
  10. Concussion Detector:
    This project deals with the detection and prevention of head injuries due to cumulative impacts and concussions. Recent advancements in concussion research in athletics has shown, the second impact to the head deals the most damage to the brain. The goal of this project is to design, build and test a cumulative impact real-time monitoring system embedded in a helmet. Head injuries are common in both contact sport players and military personnel in conflict zones, and their mismanagement can lead to repeat concussions, prolonged symptoms, and long-term consequences. A feature of this detector would be real time data aggregation and connectivity for remote health monitoring.
    University: CNU
  11. Flight Payload Recovery and Tracking System:
    The motivation for this project comes from recent events where failed rocket launches led to the loss of airborne assets such as satellites, scientific experiments, or other valuable equipment. In particular, this project considers scenarios where the launch site is close to an ocean, and thus the risk is large that the payload will be dropped into the sea where it might be lost or recovered by an adversary. To help prevent such losses, it is the objective of this project to design, build, and test a prototype tracker/recovery system, which can be attached to payloads and provide flight operators (space, military, commercial) with the ability to locate and retrieve valuable hardware and software dropped over water.
    University: CNU
  12. Low SWaP Synthetic Aperture Radar:
    In general, most Synthetic Aperture Radar (SAR) systems are large and heavy as they were designed for military reconnaissance to achieve maximum performance. In this project, the senior design team will design, build and thoroughly test a SAR system with low Size, Weight and Power (SWaP) for many different applications, such as attachable on unmanned aerial vehicles (UAV) for remote sensing and ground penetrating radar (GPR) imaging. In hardware development and testing, the transmitter will be designed to send linear frequency modulated (FM) signals and the receiver is designed to demodulate, amplify, filter and digitize the signals. The transmitter will be comprised of a ramp-function generator, a Voltage Controlled Oscillator (VCO), an attenuator and a power amplifier. Signal digitization will be implemented with an audio-sampling converter and sent to a System on Chip (SOC) for image construction. In image construction, a Range Migration Algorithm (RMA) will used to convert multiple FM pulses into a SAR images. The proposed SAR system will produce real-time, high-resolution radar images with communication centered at the S-band of 2.4 GHz. The system will be thorough tested in harsh environment with different weather conditions, light levels, humidity and temperature.
    University: GMU
  13. Autonomous Intelligent Ground Vehicles: Analysis, Design, and Implementation:
    The Intelligent Ground Vehicle Competition (www.igvc.org) includes several challenges including the Self-Drive Challenge, Auto-Nav Challenge, Design Competition, Interoperability Profiles (IOP) Challenge, and Cyber Challenge. The competition and challenges form the basis for the vehicle's operational requirements. The capstone challenges are the Self-Drive and Auto-Nav Challenges. In the Self-Drive Challenge, an autonomous electric car navigates a course that simulates many traffic situations including keeping in lane, avoiding pedestrians & obstacles, identifying & obeying traffic signs, and parking. In the Auto-Nav Challenge, a small autonomous vehicle navigates an off-road course that requires lane following, obstacle avoidance, and navigation to predetermined GPS waypoints while carrying a 20-pound payload. The IOP Challenge involves monitoring, controlling, and teleoperation of a robotic vehicle using the SAE Joint Architecture for Unmanned Systems (JAUS). In the Cyber Challenge, design involves making the vehicle's software and network interfaces resilient to security threats. Notably, the ODU team placed second in the 2019 Cyber Challenge.
    For the Auto-Nav, Little Blue V2.0, has been designed from "the ground up" beginning in the Fall of 2019 and continuing through the present as a collaboration of ECE and MAE senior design teams. During the Summer of 2022, an MAE senior design team completed a working prototype that the team can immediately use as a platform begin development upon. For the Self-Drive, the Monarch I, is a two-seat electric car consisting of a GEM e2 with aftermarket modifications that support drive-by-wire. The software systems for all vehicles will be based on the Robot Operating System (ROS).
    Design Objectives
    The principal design requirement is to meet the qualification requirements for both vehicles to participate in the 2023 IGVC. In addition, with the original release of ROS being phased out, new software development will prioritize using the ROS2 platform. Design objectives include but are not limited to:
    1. Design, implementation, and testing of vehicle sensors that support enable obstacle identification and avoidance (EE & CpE)
    2. Design, implementation, and testing of simple autonomy capable of obstacle avoidance
    3. Design, development, integration, and testing of the power and drive system (EE & CpE) for Little Blue V2.0
    4. Design & development of virtual simulation environment to test major modes of operation including processing of simulated sensor data, computer vision pipeline, and navigation (Primarily CpE)
    Some of the tasks that will help achieve objectives are:
    1. Analysis of existing sensors, electrical, and electronic systems to include recommendations for refinements and redesign, particularly for Little Blue V2.0 (EE & CpE)
    2. Development of ROS2 software applications & nodes on an Ubuntu Linux platform to receive and process sensor data including computer vision & AI to support object identification & avoidance (Primarily CpE)
    3. The introduction of Machine Learning/Artificial Intelligence (ML/AI) capabilities are welcome provided their capabilities are contained in a ROS node that is integrated into the robotic application and not demonstrations as stand-alone applications. Machine learning capabilities can be applied to object identification, computer vision, and or navigation (EE & CpE)
    4. Power & drive system analysis & design, characterization and integration of vehicle radar sensor and other sensor interfacing & calibration (Primarily EE)
    5. Design & development of autonomous operation using either custom or existing systems (e.g Autoware or the ROS2 nav2_bt_navigator navigation stack).
    6. Design & development of virtual simulation environment to test major modes of operation including processing of simulated sensor data, computer vision pipeline, and navigation (Primarily CpE)
    University: ODU
  14. Development of a Nano/Micro-Particle Detector for Use in Semiconductor Fabrication Equipment:
    The goal of the proposed project is to develop a sensitive downstream nano/micro-particle detector to be used for diagnostics and quality control of the operation of semiconductor plasma processing reactors without the need for added diagnostics equipment on the processing chamber. The detector is to be installed on the vacuum line with minimal or no effect on the pumping speed. Plasmas are extensively used in microelectronic fabrication steps, e.g., thin film deposition, etching, surface cleaning, and photoresist ashing. Various processes in microfabrication generate nano/micro-particles (particulates), and these particulates are responsible for about 75% of the total defects detected in semiconductor fabrication. The formation of particulates in plasma processing reactors is a major source of defects in semiconductor fabrication. Particulates formed in these discharges range in size from the nanometer to the micrometer. The detector is to be installed on the vacuum line with minimal or no effect on the pumping speed. This online particulate detector is based on a charging electron beam, acceleration of the charged particulates, and a sensitive image charge detection. The particulate detector will be installed on the vacuum line downstream of the processing chamber (a sputter thin film coater) and will detect the presence of particulates during operation.
    University: ODU
  15. Designing 2D quantum computers:
    Quantum computers are touted as the next generation of problem solvers, allowing to go beyond Moore's law. In this project, the students will work on designing, modeling and fabricating a 2D quantum computer based on trapped ions. This requires understanding the fundamentals of this type of quantum computer and its advantages and shortcoming compared to other available technologies. The students will then design a surface trapped ion qubit and model it to understand the influences of all parameters (voltage, electrodes, materials, etc.) on the quality of the trap including trap height and trap energy. Finally, the students will work in the clean room to fabricate such trap and assess what solutions exist based on available equipment. This project requires at least one student to have taken ECE387, microelectronic fabrication lab.
    University: ODU
  16. Inexpensive hard materials for personal armors:
    Contrary to popular belief, the most effective and simplest form of bulletproof armor for fortifications is the sandbag. Silicon dioxide is hard enough to abrade most projectiles, resulting in energy dissipation and stopping of the bullet. This has prompted the development of personal ceramic body armor; the abrasives currently in use are alumina, silicon carbide and boron carbide. While these compositions are hard, they are not flexible and thus restrict mobility. Here, we will weave mixtures of our superhard materials with polymers to create a hard and ductile composite. The ultimate goal is to develop a self-healing armor that will be able to self-report its degree of damage.
    University: VCU
  17. Doppler radar-based tracking and classification of target objects:
    The problem of existing radar is inaccuracy and unreliable for early detection and warning of incoming threats and a high accuracy estimate of their position and dynamics. The solution is to adopt the latest doppler radar integrated by RGB-D cameras with the-state-of-the-art artifice intelligence technologies. Doppler radar uses the Doppler effect to produce velocity data about objects at a distance by bouncing a microwave signal off a desired target and analyzing how the object's motion has altered the frequency of the returned signal in the form of a spectrogram. This spatiotemporal variation gives direct and highly accurate measurements of the radial component of a target's velocity relative to the radar, with the latest machine learning approaches.
    University: VCU
  18. Autonomous Nuclear Hazard Quaduped Inspection Robot:
    Ensuring the safety and security of nuclear materials is a critical need in both the defense and power sectors. There is a national security and economic need to develop autonomous nuclear inspection techniques that keep humans out of harm's way. Inspections are a significant operational cost to nuclear power plants. Not only do people cost money to employ, but they are prone to mistakes when performing repetitive and monotonous tasks. The nuclear industry is looking to address this by using robotic systems to support or replace certain tasks currently performed by humans. Of particular interest is the ability of an autonomous system to perform routine radiation measurements. The terrain can be challenging for unmanned ground vehicles, thus a quadruped-based platform would provide additional mobility when dealing with uneven facility or cave-like terrains. In this capstone project, students will design and develop the capabilities that enable a quadruped robot to autonomously navigate around a room to take radiological measurements to increase the information gained on the hazards in the room. This project requires additional algorithmic capabilities that allow the robot to identify physical hazards while performing inspections using vision and lidar sensors. Furthermore, the robot requires the electromechanical integration of radiological sensors for supporting autonomous decision making and radiological measurement maps.
    University: VCU
  19. Augmented Reality Command and Control of Autonomous Mobile Robots:
    Recently developed sensing, machine learning, and software technologies have increased the interest in deploying autonomous systems in hazardous disaster response and national security use cases. However, many of these autonomous systems require an imbalanced command and control structure: multiple humans to one autonomous robot. This challenge will get harder as more systems are deployed. To re-balance and invert this command and control structure, there is a need to develop human-centered interface and autonomy algorithms that enable the command of multiple vehicles. In this project, students will design and develop a prototype multi-robot command and control architecture that integrates an augmented reality (AR) interface. This project would require students to develop autonomy algorithms that allow the human to task the vehicles as well as support their information sharing. These efforts would apply to a use case that involves a single autonomous ground vehicle and air vehicle. The requirements to command these vehicles would shape the collaborative development of the AR interface with VCU Arts Kinetic Imaging capstone students.
    University: VCU
  20. 3d printed lower limb prosthetics:
    Producing cheap, customizable, and durable prosthetics for lower limbs is an expanding area of research due to the new progress that is being made in 3D printing technology. Given the costly and time-consuming process of making and fitting lower limb prosthetics, it would be advantageous to create design processes that produce easy-to-assemble prosthetics that are also durable for long term use. Combing material, mechanical and biomedical engineering techniques could allow for the necessary innovations needed to make prosthetics more accessible to all.
    University: VCU
  21. Fabrication of Magnetic Filaments for Fused Deposition Modeling technology:
    Advanced 3D printing of composite materials and related technologies is an incipient route to achieving functional structures while avoiding the limitations of traditional manufacturing. Against this background, fabrication of high-performance 3D printed permanent magnetic components with no limitation in shape and dimensions is highly desired to overcome current design and manufacturing restrictions which affect the efficiency of the final devices in energy, automotive, aerospace, and military sectors. However, rapid advancement in this field is hindered by the lack of availability of feedstock precursors. Addressing this need, the proposed project is focused on developing novel magnetic filaments for fused deposition modeling additive manufacturing technology.
    University: VCU
  22. The Battery Vampire:
    Every day millions of people throw out millions of alkaline batteries that end up in landfills. For example, a typical 1.5V alkaline battery will not be usable once the voltage has dropped to 1.2 - 1.3 V, and at this point is often discarded. Not only do these batteries have valuable metal content, which can be potentially recycled, they also typically have stored electrical energy remaining. This project addresses this latter issue, and seeks to efficiently recapture the stored electrical energy out of the millions of low-voltage alkaline batteries that are typically being discarded, and use it to recharge additional batteries for subsequent use. The goal would be to design a system where various size, used, low-voltage batteries can be loaded in, and then the system automatically detects the existing voltage levels and combines them as needed, to recharge a new set of batteries.
    University: VCU
  23. Macrodiversity in Future Cellular Wireless Networks:
    The aim of next-generation wireless communications will always be to improve data-rates (throughput) and cell coverage. Enhancing data-rates amounts to sending and receiving more bits of information in a given time slot, meaning faster service and greater channel capacity. Expanding cell coverage, on the other hand, means providing service to a larger number of customers with greater reliability. In the Wyner model of cellular networks, it is typical for individual cells to be serviced by single independently operating base stations, or cell towers, with no cooperation being carried out between the base stations. In this model, intercell interference is mitigated, as one user is meant to be serviced by, at most, one base station at a time. Macrodiversity, on the other hand, is a method of increasing wireless throughput and cell coverage of a network by incorporating joint signal processing between neighboring base stations opposed to independent signal processing. Utilizing multiple antennas/antenna arrays processing the same signal from spatially distributed access points results in spatial diversity and a more robust link. The joint signal processing is conducted by a central processing unit via a variety of so-called "signal combining techniques." In particular, we would like to demonstrate maximal ratio combining (MRC) and compare the bit error rate (BER) and effective wireless network coverage of the macrodiverse network to those of the traditional single base station network. We plan to show that macrodiversity is a valid candidate for improving performance in wireless networks of the future, particularly in rich-scattering environments such as warehouses, schools, office buildings, etc. In addition to the improved quality of service and coverage of the macrodiverse system, the reduced bit error rate (BER) due to joint signal processing is a direct indicator of more energy efficient communications, bringing down cost and environmental impacts of the system. As a result, we see this system having commercial and socioeconomic appeal in developing environmentally-conscious and more affordable manufacturing facilities, and work/education buildings.
    University: VCU
  24. Development of a Nuclear Reactor Simulator Interface for Engineering Education:
    The VCU Department of Mechanical and Nuclear Engineering has recently acquired the GSE Systems GPWR nuclear reactor simulator. This is a professional reactor simulator designed to accurately mimic the control room of a large, commercial, three-loop pressurized water reactor (PWR). As such, the software interface for the simulator is geared for reactor operator training as opposed to use in a university nuclear engineering program. The objective of this project is the design and development an interface for the GPWR simulator more appropriate for classroom use.
    University: VCU
  25. Treating ADHD without Medicine; Virtual Reality Workspaces:
    Using VR to help students with ADHD focus on their HW and keep on track.
    University: VCU
  26. Developing Automated Espionage Equipment:
    The focus of this project is to develop miniature devices that can automatically record conversation and send encrypted recordings to a base station. This project involves developing solutions for embedded systems such as Arduino and Raspberry Pi.
    University: VSU
  27. Connected and Autonomous RC Car on a Cartesian Street Grid:
    The objective of this project is to design and implement an autonomous RC car that can self-drive and self-localize as it moves along a signalized Cartesian grid of roads. The autonomous RC car must obey the traffic signals at each intersection and obtain information from the road infrastructure to localize itself. The autonomous RC car will be equipped with cameras that will stream video to a central server for viewing on a graphical user interface (GUI). The GUI will also show the car's location and speed on the grid in real-time. The autonomous RC car will be programmed to follow a specified route from a starting point to an end point on the grid. In coordination with the traffic signal control system, the autonomous RC car will be able to adjust its speed to minimize the number of stops at traffic lights.
    University: GMU-CCI Project
  28. Defend the Republic - Multi-Ball Capturing Robot:
    Defend The Republic is a twice-a-year Lighter-Than-Air (LTA) Robotics competition that pits 2 teams against each other in an aerial soccer-like game. Red team vs blue team compete to capture green balls (neutrally bouyant helium balloons) and score goals on the opposing team. The GMU team (The Patriot Pilots) currently does not have a robot that can capture multiple balls at a time and need new robots that can cooperatively capture, store, and release more than 1 ball simultaneously.
    University: GMU-CCI Project
  29. Spectrum Management for 5G and Radar Coexistence:
    The Federal Government operates fixed and mobile high power airborne, shipborne and terrestrial radars in the 3.1-3.7 GHz frequency band throughout the world. These radars perform functions, such as, search and tracking of near surface and high-altitude airborne projectiles, sea surveillance, and tracking of airborne objects. In order for 5G systems to co-exist with these radar systems, we need to understand radar's field of operation and ability for 5G radios to transmit. The 5G platform needs to be able to support dynamic spectrum sharing to be able to co-exist with shipborne radar. In this project, students will develop a spectrum management technique to assess the ability of 5G systems to vacate the band in presence of a transmitting radar. The resultant system will provide insights into spectrum sharing abilities of the 5G systems that will be achieve low latency, high performance and will be resilient. Students will have access to the 5G systems at ODU and radar systems at Crane for experimentation.
    University: ODU-CCI Project
  30. Multi-fusion biometric based authentication:
    The focus of this project is to develop a fully functioning biometric authentication system using multi-modal biometrics. This will entail: 1. Setting up some biometric sensor such that a biometric can be captured 2. Segmenting the captured biometric to exclude noisy data 3. Extracting biometric features for comparison
    University: VSU-CCI Project
  31. Multi-channel secure optical communication using hidden data with noise randomized encryption:
    Expansion of digital systems in the battlefield and in smart cities necessitates secure communication links and development of secure data protocols. Quantum technologies are poised to provide solutions for data security. However, noise sources already existing in the optical communication links also provide a simpler and effective way to generate secure signals when compared to complicated data encryption algorithms. This project will explore multi-channel encryption in optical communications using noise (such as amplified spontaneous emission in erbium doped fiber amplifiers) for secure data transfer (optical steganography). The noise signal is generated due to the nonlinear optical response and multiplexed or coupled into the optical communication link. The original signal can be retrieved only by the desired clients using either an identical noise dropping device (hardware key) or the specific parameters/timing of the noise generated (software key). The students in this project will setup a multi-channel optical communication link and demonstrate secure optical transmission systems using a noise-based encryption method. The outcomes of this project will pave the way for semi-quantum noise randomized data encryption. Further, the principles of random noise source data encryption established may also be expanded to secure 5G wireless transmission systems.
    University: VCU-CCI Project
  32. Traversing Mars Virtually Through Robotic Movement:
    We are going to be programming an ABB industrial robot to move LED lights in correspondence to data from the surface of Mars in order to give viewers a feeling of what it would be like to traverse the surface of Mars. Key tasks will be to interpret data from Mars and change it into robotic movements, to add supporting visualizations to surrounding walls using Unity, and to create human-like robotic movements.
    University: VCU-CCI Project
  33. Open City Project:
    The transportation and delivery of goods to suburban and some urban areas is currently achieved using tractor-trailers. But, navigating such a large vehicle autonomously, in an urban environment, presents multiple challenges.
    University: VCU-CCI Project
  34. James River Autonomous Monitoring Environmental Sensor:
    Understanding the effects of industrial and agricultural activity on US rivers is critical for developing methods and policies that support healthy ecosystems. Often these rivers are monitored with stationary systems that capture data at a single location. However, additional information about flow, temperature, salinity, etc. could be gathered at multiple points in a river using a collection of autonomous drifters. In addition to environmental data, a fleet of low-cost autonomous drifters might be able to capture additional information relevant to national security applications. In this project, students will design and develop a prototype networked autonomous river drifter. This project would require students to develop sensing, data fusion, and autonomy algorithms that allow the vehicle to execute long term monitoring missions. These systems will need to be co-designed with the drifter platform to ensure modularity and ability to navigate a turbulent river flow. Furthermore, students will explore how these systems would potentially communicate with each other, creating broader sensing coverage and a more varied data set than typical static river monitoring systems.
    University: VCU-CCI Project
 

UNIVERSITIES

  • Virginia Commonwealth University
  • Virginia Tech
  • Old Dominion University
  • George Mason University
  • Virginia State University
  • City College of New York
  • North Carolina A&T
  • Christopher Newport University
  • Penn State University