Skydio, Inc.

University of Pennsylvania

Gareth Benoit Cross

Abraham Galton Bachrach

Adam Parker Bry

Hayk Martirosyan

Jack Louis Zhu

Kristen Marie Holtz

Teodor Tomic

Peter Benjamin Henry

Yevgeniy Kozlenko

Ryan David Kennedy

Samuel Shenghung Wang

Anurag Makineni

Harrison Zheng

Josiah Timothy VanderMey

Dominic William Pattison

Vladimir Nekrasov

Bradley Matthew Solliday

Nathan Leo Bucki

Yixiao Sun

Aaron Christopher Miller

R Vijay Kumar

Jnaneshwar Das

Yash Shailesh Mulgaonkar

Chao Qu

A computer of an unmanned aerial vehicle (UAV) accesses, from a memory unit, a problem definition comprising cost functions associated with travel of the UAV. The computer causes movement of the UAV based on the cost functions. The computer adjusts one or more of the cost functions during a flight of the UAV. The computer causes further movement of the UAV based on the adjusted one or more of the cost functions.

Unmanned aerial vehicle operated based on cost functions

Described herein are systems for automated docking of an unmanned aerial vehicle. For example, some systems include an unmanned aerial vehicle including a propulsion mechanism, a battery, and a processing apparatus; and a dock including a landing surface with a funnel geometry shaped to fit a bottom surface of the unmanned aerial vehicle at a base of the funnel, wherein tapered sides of the funnel form corners at the base of the funnel, and a battery charger configured to charge the battery of the unmanned aerial vehicle while the unmanned aerial vehicle is on the landing surface, wherein conducting contacts of the battery charger are on the landing surface, positioned at the bottom of the funnel.

Automated docking of unmanned aerial vehicle

Described herein are systems for automated docking of an unmanned aerial vehicle. For example, some systems include a landing surface configured to hold an unmanned aerial vehicle; a box configured to enclose the landing surface in a first arrangement of the dock and expose the landing surface in a second arrangement of the dock; and a retractable arm, wherein the landing surface is positioned at an end of the retractable arm and the retractable arm is configured to extend to move the landing surface outside of the box and contract to pull the landing surface inside of the box.

Method of landing an unmanned aerial vehicle on a freestanding dock including a reconfigurable landing surface

A computer accesses an input element storage and an output element storage. The computer accesses a symbolic expression for output element storage as a function of the input element storage. The computer computes, using a symbolic computation engine of the computer, a symbolic expression for the tangent space Jacobian of the output element storage with respect to an input tangent space. The computer outputs the computed expression.

Computer-implemented symbolic differentiation using first-order retraction

In some examples, an aerial vehicle may determine, based on sensor information received from at least one onboard sensor, that an amount of light fails to satisfy a light threshold. Based at least in part on determining that the amount of light fails to satisfy the light threshold, the aerial vehicle is caused to takeoff at a specified trajectory and a specified acceleration for enabling navigation via an inertial measurement unit (IMU) and a satellite positioning system. Further, the aerial vehicle is directed to navigate an environment based at least on determining a relative heading of the aerial vehicle from information received from the IMU and information received from the satellite positioning system.

Low-light and no-light aerial navigation

A computer accesses a first symbolic expression for an output matrix as a function of an input matrix at a computing device comprising processing circuitry and memory. The computer computes a first Jacobian of the input matrix with respect to an input tangent space. The computer computes a second Jacobian of the output matrix with respect to the input matrix. The computer computes a third Jacobian of an output tangent space with respect to the input matrix. The computer applies symbolic matrix multiplication to the first Jacobian, the second Jacobian, and the third Jacobian to obtain a second symbolic expression for the output tangent space with respect to the input tangent space. The computer provides a representation of the second symbolic expression, the second symbolic expression representing a computed tangent-space Jacobian.

Computer-implemented computation of tangent-space jacobian

Autonomous aerial navigation in low-light and no-light conditions includes using night mode obstacle avoidance intelligence and mechanisms for vision-based unmanned aerial vehicle (UAV) navigation to enable autonomous flight operations of a UAV in low-light and no-light environments using infrared data.

Autonomous aerial navigation in low-light and no-light conditions

Autonomous aerial navigation in low-light and no-light conditions includes using night mode obstacle avoidance intelligence, training, and mechanisms for vision-based unmanned aerial vehicle (UAV) navigation to enable autonomous flight operations of a UAV in low-light and no-light environments using infrared data.

In some examples, an unmanned aerial vehicle (UAV) may determine a first acceleration of the UAV based at least on information from an onboard accelerometer received at least one of prior to or during takeoff. The UAV may determine a second acceleration of the UAV based at least on location information received via a satellite positioning system receiver at least one of prior to or during takeoff. The UAV may further determine a relative heading of the UAV based at least in part on the first acceleration and the second acceleration, and may be directed to navigate an environment based at least on the determined relative heading.

Described herein are systems for automated docking of an unmanned aerial vehicle. For example, some systems include an unmanned aerial vehicle including a propulsion mechanism, an image sensor, and processing apparatus; and a dock including a landing surface configured to hold the unmanned aerial vehicle and a fiducial on the landing surface, wherein the processing apparatus is configured to: control the propulsion mechanism to cause the unmanned aerial vehicle to fly to a first location in a vicinity of the dock; access one or more images captured using the image sensor; detect the fiducial in at least one of the one or more images; determine a pose of the fiducial based on the one or more images; and control, based on the pose of the fiducial, the propulsion mechanism to cause the unmanned aerial vehicle to land on the landing surface.

In some examples, an unmanned aerial vehicle (UAV) may receive location information via the global navigation satellite system (GNSS) receiver and may receive acceleration information via an onboard accelerometer. The UAV may determine a first measurement of acceleration of the UAV in a navigation frame of reference based on information from the accelerometer prior to or during takeoff. In addition, the UAV may determine a second measurement of acceleration of the UAV in a world frame of reference based on the location information received via the GNSS receiver prior to or during takeoff. The UAV may determine a relative heading of the UAV based on the first and second acceleration measurements. The determined relative heading may be used for navigation of the UAV at least one of during or after takeoff of the UAV.

Growing community of inventors

Belmont, CA, United States of America

Gareth Benoit Cross