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Development of a Long Range Shooting Simulator. Problem Definition. There are numerous companies that develop shooting simulators. Most companies position themselves in the military/law enforcement training space. Few companies market to private consumers.
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Problem Definition • There are numerous companies that develop shooting simulators. • Most companies position themselves in the military/law enforcement training space. • Few companies market to private consumers. • Commercially available shooting simulators: • Do not offer a long range solution. • Are cost prohibitive.
Long Range Shooting • For the purpose of our project we consider long range shooting: • To be at a distance greater than 100 yards. • To require the shooter to identify and compensate for the following variables: • Wind speed, wind direction, temperature, humidity, barometric pressure, altitude, gravity, ballistic coefficient, round weight, muzzle velocity, elevation, target speed, target direction, and the Coriolis Effect* *For distances greater than five hundred yards.
Market Analysis • Many people have used a basic shooting simulator without realizing it. • We’re planning to be a little more complex than Duck Hunt. • The best on the market: VirTra’s V-300 • 5-screens allowing for 300 degrees of immersion (MSRP $150k)
Solutions Research • We identified three possible design solutions for our project: • Sensor Net • Wii Mote • Image Processing
Solutions Research – Sensor Net • Create a large array of photo-sensors. • Fire an unfocused laser at the array. • Calculate the center of the beam based on photo-sensor information. Cons • Nearly unmanageable number of photo-sensors (7200 for a 10’ x 10’ screen). • Less accurate shot prediction. • Cost prohibitive. Pros • Relatively simplistic design. • Software development focus is primarily on long distance algorithms.
Solutions Research – Wii Mote • Utilize the Wii Mote’s IR camera by positioning it next to our projection screen. • Mount an IR LED sensor bar perpendicular to the barrel of the simulated gun. • Determine shot placement based on triangulation. Cons • At a distance of 15’ from the Wii Mote the sensor bar would need to be 18” long. • Not enough hardware design. Pros • Pre-existing hardware design found online. • Relatively cost effective solution.
Solutions Research – Image Processing* • Project a target on a screen. • Utilize a video camera to capture a laser point being fired at the target. • Determine shot placement based on Image Processing. Cons • Extensive amount of coding required. • No experience in Image Processing. • Expensive system components. • A frustrating amount of red tape. Pros • Existing systems solely rely on Image Processing. • Decent support for open source Image Processing libraries. • Challenging * Our chosen solution.
Hardware Overview • Off-the-shelf Components • Simulated Firearm • Laser Delivery System
Hardware Overview – Off-the-shelf Components • Computer • Video Camera • Video Capture Card • Video Projector • VIS Bandpass Filter
Hardware Overview – Simulated Firearm • Bolt-action & Spring-loaded • Realistic feel • Easily modifiable
Hardware Overview – Laser Delivery System • Requirements: • Must fit inside a bolt action rifle’s barrel. • Must be self-contained (internal power supply). • Must be rated Class 3A. • The laser must be pulsed at 10 milliseconds. • Spec for the lightest design possible.
Software Overview • Our program will be completed in C++ using Microsoft Visual Studio 2012 and will utilize and include: • OpenCV • Image Processing • User Interface
Software Overview - OpenCV • Open-source computer vision library. • Real-time image processing. • Written in C++ • Full interfaces in Python, Java, & Matlab
Software Overview – Image Processing • Thresholding technique for determination of shot placement: • Capture the image from the camera. • Smooth the original image using Gaussian smoothing. • Convert the color format of the image from RGB to HSV. • Threshold the HSV image based on variable criteria. • Create a binary image. • Smooth the binary image using Gaussian smoothing. • Calculate the image moment. • Store the relative X-Y position of the image moment.
Project Goals • Minimum Viable Product • Develop a real-time simulator for long-range shooting applications. • Design a self-contained system comprising video projection, user-interface, and capture system. • Utilize video image processing to determine shooting accuracy. • Develop shooting scenarios that involve static targets. • Develop algorithms to simulate the variables associated with long-range shooting. • Develop a means of storing and reporting shooting accuracy. • Develop a simulated firearm, including a laser system, with physical feedback. • Stretch Goals • Develop shooting scenarios that include dynamic targets. • Develop a simulated optics platform to work in tandem with the simulated firearm.
Current Progress • At this time we can: • Detect where a shot has been placed on a non-projected target. • Store the X-Y coordinate data of each shot from a session in a text document. • Retrieve the shot placement information from the most recent session and graphically display the results. • Project different targets on a screen.
System Testing Strategy • Iterative code testing. • Periodic UNH Radiation Safety Officer laser output power testing. • Designer evaluation. • Perspective users: • Law enforcement • Hunters • Sport Shooters (UNH Shooting Club) • Periodic consultation and testing with military-trained marksmen.
Contact Information • Sam Holdridge, University of New Hampshire- Electrical and Computer Engineering Email: swk32@wildcats.unh.edu • Matt Simon, University of New Hampshire - Electrical and Computer Engineering Email: mma49@wildcats.unh.edu