Skydio, Inc.

University of Pennsylvania

Anurag Makineni

Gareth Benoit Cross

Hayk Martirosyan

Kristen Marie Holtz

R Vijay Kumar

Jnaneshwar Das

Yash Shailesh Mulgaonkar

Chao Qu

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

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.

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.

The present subject matter relates to systems, devices, and methods for data-driven precision agriculture through close-range remote sensing with a versatile imaging system. This imaging system can be deployed onboard low-flying unmanned aerial vehicles (UAVs) and/or carried by human scouts. Additionally, the present technology stack can include methods for extracting actionable intelligence from the rich datasets acquired by the imaging system, as well as visualization techniques for efficient analysis of the derived data products. In this way, the present systems and methods can help specialty crop growers reduce costs, save resources, and optimize crop yield.

Growing community of inventors

San Jose, CA, United States of America

Anurag Makineni