# US 2021/0241645 A1 · Quantitative pilot evaluation during training > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2021/0241645 A1 - Document ID: US20210241645A1 - Status: Published application - Kind: A1 - Application number: 16/777,590 - Filed: 2020-01-30 - Published: 2021-08-05 - Earliest claimed: 2020-01-30 - Assignees: The Boeing Company - Applicants: The Boeing Company - Inventors: Can Onur; Pieter van Gils; Barend-Jan van Bruchem - Web page: https://patentgrep.com/patent/US20210241645A1 ## CPC - G09B 9/12: Motion systems for aircraft simulators - G09B 9/10: with simulated flight- or engine-generated force being applied to aircraft occupant (G09B9/28 takes precedence) - G09B 9/206: {for in-flight condition} - G09B 9/302: {the image being transformed by computer processing, e.g. updating the image to correspond to the changing point of view} - G09B 9/08: for teaching control of aircraft, e.g. Link trainer - G09B 9/44: providing simulation in a real aircraft flying through the atmosphere without restriction of its path - G09B 19/165: {Control of aircraft} - G09B: EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS (devices for psychotechnics or for testing reaction times A61B5/16; games, sports, amusements A63; projectors, projector screens G03B) ## Abstract A device for pilot training includes a memory, an interface, and one or more processors. The memory is configured to store at least one computational model of at least one human sensory system. The interface is configured to receive sensor data and aircraft state data from a flight simulator. The sensor data includes pilot activity data and motion data. The motion data is indicative of detected motion of a simulated aircraft of the flight simulator. The processor(s) are configured to process the motion data and the pilot activity data based on the at least one computational model to predict a pilot estimated aircraft state. The processor(s) are configured to determine an estimated error based on a comparison of the pilot estimated aircraft state and a detected aircraft state. The aircraft state data indicates the detected aircraft state. The processor(s) are configured to provide the estimated error to a second device. ## Claims ### Claim 1 A device for pilot training, the device comprising: a memory configured to store at least one computational model of at least one human sensory system; an interface configured to receive sensor data and aircraft state data from a flight simulator, wherein the sensor data comprises pilot activity data and motion data, and wherein the motion data is indicative of detected motion of a simulated aircraft of the flight simulator; and one or more processors configured to: process the motion data and the pilot activity data based on the at least one computational model to predict a pilot estimated aircraft state; determine an estimated error based on a comparison of the pilot estimated aircraft state and a detected aircraft state, wherein the aircraft state data indicates the detected aircraft state; and provide the estimated error to a second device. ### Claim 2 (depends on 1) The device of claim 1, wherein the pilot activity data indicates pilot monitoring activity, pilot control activity, or both. ### Claim 3 (depends on 1) The device of claim 1, wherein the at least one computational model comprises a vestibular model, a visual model, a proprioceptive model, or a combination thereof. ### Claim 4 (depends on 1) The device of claim 1, wherein the motion data comprises angular motion data, linear motion data, or both. ### Claim 5 (depends on 1) The device of claim 1, wherein the detected aircraft state comprises a detected lateral position, a detected longitudinal position, a detected altitude, a detected attitude, a detected linear motion, a detected angular motion, or a combination thereof, of the simulated aircraft. ### Claim 6 (depends on 1) The device of claim 1, wherein the aircraft state data indicates that the simulated aircraft has the detected aircraft state at a first time, and wherein the one or more processors are configured to predict the pilot estimated aircraft state based, at least in part, on determining that the pilot activity data indicates that an aircraft state indicator is in a line-of-sight of a pilot at a second time and that the second time is within a threshold duration of the first time. ### Claim 7 (depends on 6) The device of claim 6, wherein the aircraft state indicator comprises an instrument display, a simulated external environmental feature, or both. ### Claim 8 (depends on 7) The device of claim 7, wherein the instrument display comprises an altimeter, an attitude indicator, a heading indicator, an airspeed indicator, a turn coordinator, a vertical speed indicator, a latitude indicator, a longitude indicator, or a combination thereof. ### Claim 9 (depends on 7) The device of claim 7, wherein the simulated external environmental feature comprises a simulated landmark, one or more simulated stars, a simulated moon, a simulated horizon, or a combination thereof. ### Claim 10 (depends on 1) The device of claim 1, wherein the memory is further configured to store an aircraft dynamics model, and wherein the one or more processors are configured to process one or more of the aircraft state data, the motion data, or the pilot activity data based on the aircraft dynamics model to predict the pilot estimated aircraft state. ### Claim 11 A method of pilot training, the method comprising: receiving, at a device, sensor data and aircraft state data from a flight simulator, wherein the sensor data comprises pilot activity data and motion data, and wherein the motion data is indicative of detected motion of a simulated aircraft of the flight simulator; processing, at the device, the motion data and the pilot activity data based on at least one computational model of at least one human sensory system to predict a pilot estimated aircraft state; determining, at the device, an estimated error based on a comparison of the pilot estimated aircraft state and a detected aircraft state, wherein the aircraft state data indicates the detected aircraft state; and providing the estimated error to a display device. ### Claim 12 (depends on 11) The method of claim 11, wherein the pilot activity data comprises first activity sensor data received from a non-contact sensor, second activity sensor data received from a contact sensor, or both. ### Claim 13 (depends on 11) The method of claim 11, wherein the pilot estimated aircraft state comprises an estimated lateral position, an estimated longitudinal position, an estimated altitude, an estimated attitude, an estimated linear motion, an estimated angular motion, or a combination thereof, of the simulated aircraft. ### Claim 14 (depends on 11) The method of claim 11, wherein the aircraft state data indicates that the simulated aircraft has the detected aircraft state at a first time, and wherein the pilot estimated aircraft state is predicted based, at least in part, on determining that the pilot activity data indicates that an aircraft state indicator is in a line-of-sight of a pilot at a second time and that the second time is within a threshold duration of the first time. ### Claim 15 (depends on 14) The method of claim 14, wherein the aircraft state indicator comprises an instrument display, a simulated external environmental feature, or both. ### Claim 16 (depends on 15) The method of claim 15, wherein the instrument display comprises an altimeter, an attitude indicator, a heading indicator, an airspeed indicator, a turn coordinator, a vertical speed indicator, a latitude indicator, a longitude indicator, or a combination thereof. ### Claim 17 A computer-readable storage device storing instructions that, when executed by one or more processors, cause the one or more processors to initiate, perform, or control operations to: receive sensor data and aircraft state data from a flight simulator, wherein the sensor data comprises pilot activity data and motion data, and wherein the motion data is indicative of detected motion of a simulated aircraft of the flight simulator; process the motion data and the pilot activity data based on at least one computational model of at least one human sensory system to predict a pilot estimated aircraft state; determine an estimated error based on a comparison of the pilot estimated aircraft state and a detected aircraft state, wherein the aircraft state data indicates the detected aircraft state; and provide the estimated error to a device. ### Claim 18 (depends on 17) The computer-readable storage device of claim 17, wherein the detected aircraft state comprises a detected lateral position, a detected longitudinal position, a detected altitude, a detected attitude, a detected linear motion, a detected angular motion, or a combination thereof, of the simulated aircraft. ### Claim 19 (depends on 18) The computer-readable storage device of claim 18, wherein the pilot estimated aircraft state comprises an estimated lateral position, an estimated longitudinal position, an estimated altitude, an estimated attitude, an estimated linear motion, an estimated angular motion, or a combination thereof, of the simulated aircraft. ### Claim 20 (depends on 19) The computer-readable storage device of claim 19, wherein the estimated error is based on one or more of a difference between the detected lateral position and the estimated lateral position, the detected longitudinal position and the estimated longitudinal position, the detected altitude and the estimated altitude, the detected attitude and the estimated attitude, the detected linear motion and the estimated linear motion, or the detected angular motion and the estimated angular motion.