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Tech Briefs: April 2018

Laser Detecting Systems Enhancing Survivability and Lethality on the Battlefield Designing With Plastics for Military Equipment Engine Air-Brakes Paving the Way to Quieter Aircraft Nett Warrior Enhancing Battlefield Connectivity and Communications XPONENTIAL 2018 - An AUVSI Experience Communications in Space: A Deep Subject First Air-Worthy Metal-Printed RF Filter Ready for Takeoff Validation of Automated Prediction of Blood Product Needs Algorithm Processing Continuous Non-Invasive Vital Signs Streams (ONPOINT4) Using a combination of non-invasive sensors, advanced algorithms, and instruments built for combat medics could reduce hemorrhaging and improve survival rates. Calculation of Weapon Platform Attitude and Cant Using Available Sensor Feedback Successful development of mobile weapon systems must incorporate operation on sloped terrain.
Journal Article

Algorithm Development for Avoiding Both Moving and Stationary Obstacles in an Unstructured High-Speed Autonomous Vehicular Application Using a Nonlinear Model Predictive Controller

Abstract The advancement in vision sensors and embedded technology created the opportunity in autonomous vehicles to look ahead in the future to avoid potential obstacles and steep regions to reach the target location as soon as possible and yet maintain vehicle safety from rollover. The present work focuses on developing a nonlinear model predictive controller (NMPC) for a high-speed off-road autonomous vehicle, which avoids undesirable conditions including stationary obstacles, moving obstacles, and steep regions while maintaining the vehicle safety from rollover. The NMPC controller is developed using CasADi tools in the MATLAB environment. The CasADi tool provides a platform to formulate the NMPC problem using symbolic expressions, which is an easy and efficient way of solving the optimization problem. In the present work, the vehicle lateral dynamics are modeled using the Pacejka nonlinear tire model.