AeroPod

This innovative kite system is called the WindiWing, and utilizes aerodynamic forces and moments to control its configuration for both ascent and descent, eliminating the need for an external power source or human intervention. By harnessing wind power, the system autonomously climbs and descends along a pilot kite line, provided sufficient wind conditions exist. Windiwing includes a set of stops at predetermined upper and lower bounds of the kite line, which define the highest and lowest points the WindiWing can travel. When a stop is hit, the WindiWing changes direction. Therefore, it can sustain extended flight times at different altitudes. Unlike prior solutions, WindiWing is a passive line-climber operating entirely through aero-mechanical principles and does not require electrical power or active control systems for changes in lift. Instead, WindiWing continuously moves between the designated stops along the kite tether, maintaining stable and predictable movement without the need for remote operation or onboard power. WindiWing is designed with flexibility in mind, offering the ability to carry a range of instrumentation, making it suitable for integration with kite-based systems, tethered balloons, or uncrewed aircraft platforms. The absence of electrical components reduces complexity, enhances reliability, and allows for extended atmospheric data collection with minimal oversight. By offering a scalable, cost-effective, and power-independent solution, this technology enables long-duration atmospheric profiling at various altitudes, making it an ideal tool for researchers in the fields of atmospheric research, environmental research, and education.

Increasing demand for smaller UAVs (e.g., sometimes with wingspans on the order of six inches and weighing less than one pound) generated a need for much smaller flight and sensing equipment. NASA Langley's new sensing and flight control system for small UAVs includes both an active flight control board and an avionics sensor board. Together, these compare the status of the UAVs position, heading, and orientation with the pre-programmed data to determine and apply the flight control inputs needed to maintain the desired course. To satisfy the small form-factor system requirements, micro-electro-mechanical systems (MEMS) are used to realize the various flight control sensing devices. MEMS-based devices are commercially available single-chip devices that lend themselves to easy integration onto a circuit board. The system uses less energy than current systems, allowing solar panels planted on the vehicle to generate the systems power. While the lightweight technology was designed for smaller UAVs, the sensors could be distributed throughout larger UAVs, depending on the application.

The technology presents an on-board estimation, navigation and control architecture for multi-rotor drones flying in an urban environment. It consists of adaptive algorithms to estimate the vehicle's aerodynamic drag coefficients with respect to still air and urban wind components along the flight trajectory, with guaranteed fast and reliable convergence to the true values. Navigation algorithms generate feasible trajectories between given way-points that take into account the estimated wind. Control algorithms track the generated trajectories as long as the vehicle retains a sufficient number of functioning rotors that are capable of compensating for the estimated wind. The technology provides a method of measuring wind profiles on a drone using existing motion sensors, like the inertial measurement unit (IMU), rate gyroscope, etc., that are observably necessary for any drone to operate. The algorithms are used to estimate wind around the drone. They can be used for stability or trajectory calculations, and are adaptable for use with any UAV regardless of the knowledge of weight and inertia. They further provide real-time calculations without additional sensors. The estimation method is implemented using onboard computing power. It rapidly converges to true values, is computationally inexpensive, and does not require any specific hardware or specific vehicle maneuvers for the convergence. All components of this on-board system are computationally effective and are intended for a real time implementation. The method's software is developed in a Matlab/Simulink environment, and has executable versions, which are suitable for majority of existing onboard controllers. The algorithms were tested in simulations.

This UAS technology defines a part-time VTOL system that transitions to efficient fixed-wing operation to obtain desired endurance and range. A novel three-segment wing design includes: a fixed Inner segment mounted to the fuselage, a controlled, articulating intermediate segment to which lift engines are attached, and a free-to-rotate outer segment to alleviate gust impacts on the airframe in both modes. The aft propulsor is articulated and configured such that the thrust being generated is always in a proverse direction. Also, the controlled-articulation wing segments are operated in both tandem and differential modes to allow for direct control while in the various modes of operation. Also incorporated is a novel control architecture that encompasses both the different system operating modes as well as the considerable number of individual control options and combinations.

The TerraROVER’s core functionality is centered around its electric propulsion system, enabling it to traverse various outdoor environments. Its drive system consists of electric motors and gearboxes that provide controlled speed and maneuverability. The remote-control interface allows users to adjust speed and direction, making it an effective platform for training and testing mobility systems. For advanced applications, the TerraROVER can be adapted for pre-programmed or autonomous navigation, expanding its use in robotics and automation research. A key design feature of the TerraROVER is its adaptability for sensor integration. It includes mounting provisions for miniaturized sensors capable of capturing environmental data such as temperature, GPS location, and visual imagery. The platform supports both onboard data logging and real-time transmission, making it suitable for field studies, distributed sensing applications, and educational experiments. Fabrication is streamlined through the use of 3D-printed components, allowing for cost-effective production and easy assembly in classroom or research settings. Currently at Technology Readiness Level (TRL) 7, the system has been successfully demonstrated in an operational environment and is available for patent licensing.