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US-12625507-B2 - System and method for tilt dead reckoning

US12625507B2US 12625507 B2US12625507 B2US 12625507B2US-12625507-B2

Abstract

A system and method for tilt dead reckoning is provided. The system and method allows an autopilot of an unmanned aerial vehicle (UAV) to perform dead reckoning with a hovering vehicle during GNSS signal loss by estimating the position and velocity of the vehicle based on its pitch and roll angles and known vehicle dynamics. The position and velocity are estimated using tables set up by a UAV integration engineer that provide the expected airspeed at given pitch and roll angles in steady state. This allows the UAV to attempt to follow waypoints when GNSS signal is lost without using any additional sensors.

Inventors

  • Tyler Desmond MELMOTH
  • Howard William LOEWEN

Assignees

  • 4596286 Manitoba Ltd

Dates

Publication Date
20260512
Application Date
20241219

Claims (13)

  1. 1 . A method of hovering dead reckoning for GNSS (Global Navigation Satellite System) denied navigation of unmanned aerial vehicles (UAV) having fixed lifting rotors while hovering, the method comprising: estimating a wind velocity; determining the UAV's pitch and roll; converting the UAV's estimated velocity, added to the wind velocity, into a lateral equilibrium force using one or more tables or formulas; calculating a lateral acceleration of the UAV; integrating the lateral acceleration into a change in velocity of the UAV; updating the UAV's estimated velocity by adding the change in velocity of the UAV; integrating the UAV's updated estimated velocity to obtain a position estimate of the UAV; providing the position estimate of the UAV to a navigation system; and controlling the UAV using the updated velocity and the position estimate.
  2. 2 . The method of claim 1 , wherein the step of calculating the lateral acceleration includes calculating lateral acceleration from the determined UAV pitch and roll angles and then subtracting the lateral equilibrium force converted into an acceleration using the UAV's mass.
  3. 3 . The method of claim 1 , where the step of calculating the lateral acceleration includes: calculating a lateral force from the determined UAV pitch and roll and UAV mass, and then subtracting the lateral equilibrium force; converting the resulting lateral force into a lateral acceleration by dividing by the UAV mass.
  4. 4 . The method of claim 1 wherein the lateral equilibrium force is calculated from the UAV's pitch and roll using one table or formula for the UAV's estimated velocity.
  5. 5 . The method of claim 1 wherein the lateral equilibrium force is calculated from the UAV's pitch and roll using two tables or formulas, one for the UAV's X velocity and one for the UAV's Y velocity.
  6. 6 . The method of claim 1 , where the step of estimating the wind velocity is performed prior to loss of GNSS signal and includes: converting the UAV's pitch and roll to an estimated airflow velocity in a body frame; transforming the estimated airflow velocity to a world frame; subtracting a velocity estimate in the world frame from the estimated airflow velocity in the world frame to estimate the wind velocity in the world frame; and applying a low-pass filter to the estimated wind velocity to determine a filtered wind velocity.
  7. 7 . The method of claim 6 , wherein the wind estimate is based on the estimated airflow velocity when the UAV is hovering, moving at a constant speed or accelerating.
  8. 8 . A method of dead reckoning for GNSS (Global Navigation Satellite System) denied navigation of unmanned aerial vehicles (UAV) having fixed lifting rotors while hovering, the method comprising: estimating a wind velocity; measuring the UAV's pitch and roll; converting the UAV's estimated velocity, added to the wind velocity, into an equilibrium pitch and roll using one or more tables or formulas; calculating an excess pitch and roll by subtracting the calculated equilibrium pitch and roll from the measured pitch and roll; calculating an acceleration from the excess pitch and roll; integrating the acceleration into a change in velocity of the UAV; updating the UAV's estimated velocity by adding the change in velocity of the UAV; integrating the UAV's updated estimated velocity to obtain a position estimate of the UAV; providing the position estimate of the UAV to a navigation system and controlling the UAV using the updated velocity and the position estimate.
  9. 9 . The method of claim 8 , where the step of estimating the wind velocity is performed prior to loss of GNSS signal and includes: converting the UAV's pitch and roll to an estimated airflow velocity in a body frame; transforming the estimated airflow velocity to a world frame; subtracting a velocity estimate in the world frame from the estimated airflow velocity in the world frame to estimate the wind velocity in the world frame; and applying a low-pass filter to the estimated wind velocity to determine a filtered wind velocity.
  10. 10 . The method of claim 9 , wherein the wind estimate is based on the estimated airflow velocity when the UAV is hovering, moving at a constant speed or accelerating.
  11. 11 . An unmanned aerial vehicle (UAV), the UAV comprising: fixed lifting rotors while hovering; a processor; a memory for storing one or more tables having expected airflow velocity for different pitch and roll angles; the processor being configured to: estimate a wind velocity; determine the UAV's pitch and roll; convert the UAV's estimated velocity, added to the wind velocity, into a drag acceleration using one or more tables or formulas; calculate an acceleration from the determined UAV pitch and roll and then subtracting the drag acceleration; integrate the acceleration into a change in velocity of the UAV; update the UAV's estimated velocity by adding the change in velocity of the UAV; integrate the UAV's updated estimated velocity to obtain a position estimate of the UAV; providing the position estimate of the UAV to a navigation system; and control the UAV using the updated velocity and the position estimate.
  12. 12 . The UAV of claim 11 , wherein the drag acceleration is calculated from the UAV's pitch and roll using one table or formula for the UAV's velocity.
  13. 13 . The UAV of claim 11 , wherein the drag acceleration is calculated from the UAV's pitch and roll using, a first table or formula for the UAV's X velocity and a second table or formula for the UAV's Y velocity.

Description

TECHNICAL FIELD The present application relates to a dead reckoning system and method. More particularly, the present application relates to a tilt dead reckoning system and method for unmanned aerial vehicles (UAV). BACKGROUND Unmanned aerial vehicles (UAV) are generally any aircraft that is does not have an onboard human pilot. UAVs may be of various sizes and configurations, including hovering and non-hovering vehicles. UAVs may be fully autonomous or may be controlled wholly or in part by a human operator. UAVs may also include (and be referred to as) drones, unmanned aerial systems (UAS) and remotely piloted aerial systems (RPAS). Conventional solutions for calculating dead reckoning of UAVs use inertial navigation where onboard gyros and accelerometers measure the UAV's angular rotation rate and acceleration. The angular rate is integrated over time to give an estimate of the UAV's orientation, which may be corrected by measurements from the accelerometers or other sources. The acceleration from the accelerometers is transformed to the world frame using the orientation estimate, the estimated gravity vector is subtracted and the result is integrated over time to give a velocity estimate, and the velocity estimate is integrated over time to give a position estimate. One problem with inertial navigation is that errors in the estimated orientation or measured acceleration cause the error in position to increase with the cube or square of time, so a small error in acceleration or orientation can quickly lead to a very large position error. US20150197335 discusses a control system configured to control an acceleration of an air vehicle which comprises a tiltable propulsion unit that is tiltable to provide a thrust whose direction is variable at least between a general vertical thrust vector direction and a general longitudinal thrust vector direction with respect to the air vehicle. US20200141969 discusses a method of determining airspeed of a movable object, the method includes performing a calibration process to determine a relationship between forces exerted on the movable object and airspeed of the movable object, determining forces exerted on the movable object while the movable object is moving, and determining an airspeed of the movable object based on the determined forces and the relationship. US20150202540 discusses a hand-held radio transmit controller for remotely controlling an aircraft, and a method for controlling a remote control aircraft offering ground vehicle-like control. The following are examples of situations and environments that need an improved system and method of dead reckoning. Example 1: Global navigation satellite system (GNSS) signal intentionally blocked at a factory. A multirotor is flying around a factory checking the perimeter as a result of a security alarm. As it reaches the northwest corner of the factory GNSS reception is lost due to a GNSS jammer placed on the ground by the intruders. The operator takes control in a camera guide mode, completes the inspection manually and identifies the location of the GNSS jammer. The operator then switches the multirotor back to autonomous mode. The multirotor still does not have GNSS signal and so it enters hover dead reckoning mode and heads towards its ditch location. Halfway to the ditch location it is beyond the range of the jammer and so GNSS reception is regained and the multirotor returns home and lands. Example 2: Multirotor loses GNSS reception due to a hardware fault. A multirotor is flying around a factory checking emissions. A permanent fault in the GNSS receiver causes a loss of GNSS position and velocity information. The vehicle hovers for a few seconds to see if the GNSS signal will be reacquired. When it does not reacquire the GNSS signal, the multirotor enters hover dead reckoning mode. The multirotor flies to its ditching point a kilometer from the factory. As the multirotor approaches the ditching point, the autopilot pitches up to slow down and stop. The multirotor then starts a slow descent while holding the appropriate pitch and roll for zero velocity. During the descent the velocity of the multirotor starts to slow but it does not stop before it reaches the ground. Six inches above the ground the autopilot cuts complete power to the motors. The multirotor drops to the ground and tips over causing minor damage. Example 3: Helicopter loses GNSS signal over a city due to hardware fault. An autonomous helicopter is flying over a city when it loses GNSS signal. The helicopter enters hover dead reckoning mode and starts flying towards its ditching location twenty kilometers away at a speed of 40 kilometers an hour. After a half hour flight, it reaches its ditching location, descends to an altitude where it will cut the engine. Once the engine is stopped the helicopter falls to the ground at a safe location. Example 4: Helicopter loses GNSS signal over city and lands on the top of the building. A helicopter is fly