Sikorsky Aircraft Corporation

Raytheon Technologies Corporation

United Technologies Corporation

Goodrich Corporation

Thomas A Frewen

Harshad S Sane

Ozgur Erdinc

Mei Chen

Draguna Vrabie

Hala Mostafa

Brendan Englot

Kunal Srivastava

Jason C Derenick

Lawrence E Zeidner

A method and system of providing customizable service for an asset. The method including generating a predictive model for each asset of a fleet, each predictive model based on an operational profile for the asset and including a probability density function associated with the operational durability of the asset, establishing a maintenance strategy associated with the asset, and combining each of the predictive models to generate a compound fleet performance model, the fleet performance model including a combined probability density function. The method also includes collecting actual asset performance and maintenance data to generate actual asset metrics, determining a fleet performance profile based on the actual asset metrics indicative of a health assessment of the fleet, comparing the predicted fleet performance with the actual fleet performance, and ascertaining actionable choices for managing the assets based on a deviation of the predicted and actual fleet performance.

Method for online service policy tracking using optimal asset controller

Systems and methods for the configuration of service policies for aircraft fleets and gas turbine engines are disclosed. One or more engine performance profiles may be generated based on historical engine performance data. The historical engine performance data may be retrieved based on one or more engine service parameters. A fleet performance profile may be generated based on the engine performance profiles. The engine service parameters may be varied to generate a configured engine performance profile. A configured fleet performance profile may be generated based on the configured engine performance profile.

Aircraft fleet and engine service policy configuration

The present disclosure provides a flexibly positioned power drive unit ('PDU) system. The flexibly positioned PDU system may comprise a flexibly positioned PDU comprising a PDU hinged portion and a track coupled to the flexibly positioned PDU, wherein the flexibly positioned PDU is configured to move along a cargo deck and the PDU hinged portion is configured to move a cargo unit from a first location to a second location via the track.

Aircraft cargo handling system with self-organizing flexibly positioned power drive units

An aspect includes space partitioning for vehicle motion planning. A plurality of obstacle data is analyzed to determine a plurality of obstacle locations in a configuration space of a vehicle. A partitioning of the configuration space is performed to compute a skeletal partition representing a plurality of obstacle boundaries based on the obstacle locations. The skeletal partition is used to preferentially place a plurality of samples by a sampling-based motion planner. At least one obstacle-free path is output by the sampling-based motion planner based on the samples.

Space partitioning for motion planning

A method of operating an obstacle data model construction system of an aircraft is provided. With a vehicle moving through a vehicle obstacle space from a first to a second position, the method includes scanning the vehicle obstacle space at the first and second positions, generating first and second boundary data sets from results of the scanning at the first and second positions, respectively, and deriving first and second shrouded regions from the first and second boundary data sets, respectively. The method further includes identifying a high confidence occupancy region from intersecting portions of the first and second shrouded regions or identifying an occupancy region from a union of the first and second shrouded regions.

Obstacle data model construction system with range sensor shadows and use in motion planning

A method of route planning for a vehicle proceeding from a current location to a destination in a planning space is provided. The method includes generating a destination-rooted tree from global information that provides cost-to-go routing to the destination from multiple locations in the planning space, generating a vehicle-rooted tree using local information from the current location out to a sensing horizon and determining a local destination at the sensing horizon. The local destination corresponds to minimal cost-to-go routing obtained from the destination-rooted tree.

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West Hartford, CT, United States of America

Thomas A Frewen