Abstract: Described herein are modified NK-92 cells comprising a genetic alteration to decrease beta-2-microglobulin (B2M) expression in NK-92 cells to reduce the levels of HLA class I expression; methods of generating such cells; and methods of treating a subject, e.g., that has cancer, with the B2M-modified NK-92 cells.

Abstract: A system and a method for generating a 3D path from a source to a destination for an aerial vehicle is disclosed. An example system includes a managing unit to select a group of altitude layers including source and destination and generate a 2D horizontal scenario by identifying constraints to avoid at each altitude layer. The example system includes a path computing unit to determine common constraints for the altitude layers of the 2D horizontal scenario and compute a 2D lateral path avoiding the common constraints. The managing unit generates a 2D vertical scenario based on a projection of the previously computed 2D lateral path onto the constraints at the altitude layers. The path computing unit computes a 2D vertical path avoiding constraints of the 2D vertical scenario. The managing unit composes 3D waypoints of a conflict-free 3D path according to the 2D lateral path and 2D vertical path.

Abstract: The invention relates to a method for computing a bound B up to a given confidence level 1??, of an error in a state vector estimation KSV of a state vector TSV of a physical system as provided by a Kalman filter. The method decomposes the errors of the Kalman solution as a sum of the errors due to each of the measurement types used in the filter, In addition, the contribution of each type of measurement is bounded by a multivariate t-distribution that considers the error terms from all the epochs processed. Then, the method implements three main operations: computing a probability distribution of the measurement errors for each epoch and measurement type; summing the previous distributions to obtain a global distribution that models the Kalman solution error; and computing the error bound B for a given confidence level from the resulting distribution.

Abstract: A computer-implemented method and a system for communicating high fidelity (HIFI) trajectory-related information of an aerial vehicle (AV) through standard aircraft trajectory conventions is disclosed. The method includes obtaining, from a first entity, a flight intent containing low fidelity (LOFI) trajectory-related information. The method also includes obtaining intent generation (IG) configuration parameters defining constraints, objectives, or a combination thereof, supplementary to the flight intent, the IG configuration parameters containing HIFI trajectory-related information for closing all degrees of freedom of motion of the AV and configuration. The method includes encoding, using standard aircraft trajectory conventions, the LOFI trajectory-related information from the flight intent and IG configuration parameters as a flight plan and user-defined fields available for information exchange. The method further includes sending, to a second entity, the flight plan and the user-defined fields.

Abstract: Example air vehicle navigation systems and methods are described herein that utilize a Common Runtime Aircraft Intent Data Structure (CRAIDS). An example method includes determining an initial condition of a flight of an air vehicle, determining a flight constraint, determining, using a common runtime aircraft intent data structure (CRAIDS), an aircraft trajectory based on the initial condition and the flight constraint, and performing the determined aircraft trajectory during the flight of the air vehicle.

Abstract: Methods and apparatus of tracking moving targets from air vehicles are disclosed. An example system includes an air vehicle including a moving target state estimator to determine at least one of an estimated speed or an estimated location of a moving target, a tracking infrastructure to determine a detectability zone surrounding the moving target based on at least one of the estimated speed or the estimated location of the moving target, and generate a guidance reference to command the air vehicle to move towards a reference location, the reference location based on the estimated location, and a flight control system to cause the air vehicle to follow the moving target outside of the detectability zone based on the guidance reference.

Abstract: Computer-implemented method and system for modelling performance of a fixed-wing aerial vehicle (AV) with six degrees of freedom. The system comprises a collecting unit (330) to collect data from a plurality of modelling measures and modelling maneuvers; a processing unit (340) to communicate with a collecting unit (330). The processing unit (340) further sequentially processes data sets from a plurality of modelling measures and to determine models to generate an accurate APM. Modelling measures and modelling maneuvers are designed to modify an influence on the of variables of a model of the AV (100).

Abstract: Methods and apparatus of tracking moving targets from air vehicles are disclosed. An example method in response to an estimated speed and an estimated location of a moving target, determines a detectability zone surrounding the moving target; and causes an air vehicle to follow the moving target outside of the detectability zone.

Abstract: Apparatus to generate aircraft intent and related methods are disclosed.

Abstract: Methods and systems for autonomous generation of shortest lateral paths for unmanned aerial systems are described. An example system includes memory storing code and at least one processor to execute the code to cause the at least one processor to access an initial scenario including a source point, a target point, and a no flight zone, determine a computation time for identifying a lateral path for an aircraft to traverse that avoids the no flight zone, determine whether the determined computation time satisfies a threshold of a reference computation time, change the first number of vertices to a second number of vertices when the reference computation time is not satisfied, determine a buffer area surrounding the no flight zone, construct a visibility graph including lateral paths, and identify one of the lateral paths as being shorter than others of the lateral paths.

Abstract: Example aircraft intent processors are described herein that can be used both for the prediction of an aircraft's trajectory from aircraft intent, and the execution of aircraft intent for controlling the aircraft. An example aircraft intent processor includes an aircraft intent input to receive aircraft intent data representative of aircraft intent instructions, an aircraft state input to receive state data representative of a state of the aircraft, and a residual output. The aircraft intent processor is to calculate residual data representative of an error between a state of the aircraft commanded by the received aircraft intent data and the state of the aircraft expressed by received state data, and output the residual data via the residual output.

Abstract: Methods and systems for autonomous generation of shortest lateral paths for unmanned aerial systems are described. An example method includes defining an area between a source point and a target point; identifying a first no flight zone within the area; identifying a second no flight zone outside of the area; estimating a first computation time to determine a first lateral path between the source point and the target point, the estimating to consider the first no flight zone, the estimating not to consider the second no flight zone; comparing the first computation time to a reference computation time; in response to the first computation time not satisfying a threshold of the reference computation time, modifying the first no flight zone to be a third no flight zone; and estimating a second computation time to determine a second lateral path between the source point and the target point, the estimating to consider the third no flight zone.

Abstract: Apparatus to generate aircraft intent and related methods are disclosed.

Abstract: Example navigation aids for increasing the accuracy of a navigation system are disclosed herein. An example method disclosed herein identifying, with an aircraft intent description language (AIDL) aid, an AIDL instruction as associated with a first dynamic activity level of a plurality of dynamic activity levels and determining, with the AIDL aid, an aircraft state to be affected by the AIDL instruction. The example method also includes changing, with a navigation filter, a weighting scheme for a measurement of the aircraft state obtained by an inertial navigation system (INS) of the aircraft and estimating, with the navigation filter, a trajectory of the aircraft based on the weighting scheme and the measurement.

Abstract: The method of the present invention comprises acquiring input data of both aircraft performance characteristics and atmospheric data, and defining trajectory parameters to which the aircraft trajectory must be subjected, the method further comprising defining aircraft trajectory parameters; acquiring a plurality of atmospheric forecast ensembles; calculating a predicted trajectory from each atmospheric forecast of an atmospheric forecast ensemble, said predicted trajectory having associated information regarding a certain figure of merit of the aircraft trajectory, wherein an ensemble of predicted trajectories is obtained from each atmospheric forecast ensemble, each predicted trajectory of the ensemble of predicted trajectories having an associated probability derived from the probability of each atmospheric forecast within an atmospheric forecast ensemble; the system of the present disclosure comprising all the necessary equipment to carry out the method of the present disclosure.

Abstract: Example aircraft intent processors are described herein that can be used both for the prediction of an aircraft's trajectory from aircraft intent, and the execution of aircraft intent for controlling the aircraft. An example aircraft intent processor includes an aircraft intent input to receive aircraft intent data representative of aircraft intent instructions, an aircraft state input to receive state data representative of a state of the aircraft, and a residual output. The aircraft intent processor is to calculate residual data representative of an error between a state of the aircraft commanded by the received aircraft intent data and the state of the aircraft expressed by received state data, and output the residual data via the residual output.

Abstract: Example aircraft intent processors are described herein that can be used both for the prediction of an aircraft's trajectory from aircraft intent, and the execution of aircraft intent for controlling the aircraft. An example aircraft intent processor includes an aircraft intent input to receive aircraft intent data representative of aircraft intent instructions, an aircraft state input to receive state data representative of a state of the aircraft, and a residual output. The aircraft intent processor is to calculate residual data representative of an error between a state of the aircraft commanded by the received aircraft intent data and the state of the aircraft expressed by received state data, and output the residual data via the residual output.

Abstract: Methods and systems for autonomous generation of shortest lateral paths for unmanned aerial systems are described. An example method includes defining an area between a source point and a target point; identifying a first no flight zone within the area; identifying a second no flight zone outside of the area; estimating a first computation time to determine a first lateral path between the source point and the target point, the estimating to consider the first no flight zone, the estimating not to consider the second no flight zone; comparing the first computation time to a reference computation time; in response to the first computation time not satisfying a threshold of the reference computation time, modifying the first no flight zone to be a third no flight zone; and estimating a second computation time to determine a second lateral path between the source point and the target point, the estimating to consider the third no flight zone.

Abstract: Apparatus to generate aircraft intent and related methods are disclosed.

Abstract: Example air vehicle navigation systems and methods are described herein that utilize a Common Runtime Aircraft Intent Data Structure (CRAIDS). An example method includes determining an initial condition of a flight of an air vehicle, determining a flight constraint, determining, using a common runtime aircraft intent data structure (CRAIDS), an aircraft trajectory based on the initial condition and the flight constraint, and performing the determined aircraft trajectory during the flight of the air vehicle.