CN-122029104-A - Unmanned aerial vehicle-based payload management

Abstract

A drone-based payload management system includes at least one drone and a drone controller, the drone(s) having first and second payload cabins configured to store first and second payloads, respectively. The drone controller may be coupled to the payload bay and include at least one processor and at least one computer-readable memory. The memory(s) may store software instructions executable by the processor(s) to perform operations including obtaining a location of the drone(s) when the drone(s) are deployed, determining a ground attribute value of a ground surface associated with the location, deriving a payload ratio of a first amount of a first payload relative to a second amount of a second payload based on the ground attribute value, and causing the first payload bay and the second payload bay to release the first amount of the first payload and the second amount of the second payload, respectively, according to the payload ratio.

Inventors

• Patrick Thorne Song Xiong
• John Vyachek
• Nicholas J. Wikei

Assignees

• 南特知识产权控股有限责任公司

Dates

Publication Date

20260512

Application Date

20240829

Priority Date

20230912

Claims (20)

1. 1. A drone-based payload management system, comprising: at least one drone having a first payload bay and a second payload bay, wherein the first payload bay is configured to store a first payload and the second payload bay is configured to store a second payload, and A drone controller coupled with the first payload bay and the second payload bay and including at least one processor and at least one computer-readable memory storing software instructions executable by the at least one processor to perform operations comprising: obtaining a position of the at least one unmanned aerial vehicle when the at least one unmanned aerial vehicle is deployed; Determining a ground attribute value for a ground surface associated with the location; deriving a payload ratio of a first amount of the first payload relative to a second amount of the second payload based on the ground attribute value, and Causing the first payload bay and the second payload bay to release the first amount of the first payload and the second amount of the second payload, respectively, according to the payload ratio.
2. 2. The system of claim 1, wherein the ground property value complies with a ground property namespace or ontology.
3. 3. The system of claim 1, wherein the ground property value quantifies one or more properties selected from the group consisting of chemical properties, altitude properties, grade properties, physical properties, optical properties, and geographic properties.
4. 4. The system of claim 1, wherein the at least one unmanned aerial vehicle comprises at least one Unmanned Aerial Vehicle (UAV).
5. 5. The system of claim 1, wherein at least one of the first and second amounts comprises an amount released per unit time or per unit area.
6. 6. The system of claim 1, wherein the ground attribute value is derived at least in part from an image descriptor.
7. 7. The system of claim 1, wherein the payload ratio is derived from the ground property values via one or more selected from the group consisting of a look-up table, a function, and a machine learning model.
8. 8. The system of claim 1, wherein one or both of the first payload bay and the second payload bay comprises a controllable payload opening coupled with the drone controller.
9. 9. The system of claim 1, wherein the location comprises one or more selected from the group consisting of a geographic location, a postal code, a geofencing area, a Schneider 2 (S2) unit, a grid location, a fixed location, a relative location, a landmark, a simultaneous localization and mapping (SLAM) location, a visual simultaneous localization and mapping (vSLAM) location, a wireless triangle point, and/or a location relative to one or more beacons.
10. 10. The system of claim 1, wherein the obtaining comprises obtaining a location of the at least one drone while the at least one drone is flying.
11. 11. The system of claim 1, wherein the first and second amounts are measured by weight.
12. 12. The system of claim 1, wherein the first and second amounts are measured by volume.
13. 13. The system of claim 1, wherein the payload ratio is in a range of 1:100 to 1:1.
14. 14. The system of claim 1, wherein one or both of the first payload and the second payload comprise a seed.
15. 15. The system of claim 1, wherein one or both of the first payload and the second payload comprise spores.
16. 16. The system of claim 1, wherein one or both of the first payload and the second payload comprises one or more payloads selected from the group consisting of fertilizers, pesticides, liquids, powders, slurries, conditioners, worms, biologicals, and mycorrhizal fungi.
17. 17. The system of claim 1, wherein the second payload comprises calcium carbonate.
18. 18. The system of claim 17, wherein the second payload comprises oolitic aragonite.
19. 19. The system of claim 1, further comprising one or more sensors, wherein the surface attribute value is determined based on an output from at least one sensor among the one or more sensors.
20. 20. The system of claim 19, wherein the one or more sensors comprise one or more types of sensors selected from the group consisting of a GPS sensor, an accelerometer, a LIDAR sensor, a RADAR sensor, a camera, a thermometer, a magnetometer, a gyroscope, an Inertial Measurement Unit (IMU), and a spectrometer.

Description

Unmanned aerial vehicle-based payload management Cross Reference to Related Applications Is not suitable for Is not suitable for Background Technical field the technical field of the present disclosure is based on unmanned aerial vehicle payload delivery (delivery). In the agricultural sector, unmanned aerial vehicle technology has provided new institutions for sowing and spraying crops. The use of Unmanned Aerial Vehicles (UAVs) has not only begun to automate the application of seeds and fertilizer, but has also introduced ways to collect data about the ground, which have been used to make intelligent spray decisions. However, such conventional techniques do not provide an effective means for deploying soil additives (e.g., oolitic aragonite) that exhibit complex interactions with other payloads and require high flexibility and control in terms of their relative amounts and other deployment parameters. Disclosure of Invention The present disclosure contemplates various systems and methods for overcoming the aforementioned drawbacks in the known related art. One aspect of an embodiment of the present disclosure is a drone-based payload management system. The system may include at least one drone and a drone controller. The at least one drone may have a first payload bay and a second payload bay configured to store a first payload and a second payload, respectively. The drone controller may be coupled with the first payload bay and the second payload bay and may include at least one processor and at least one computer-readable memory. At least one computer readable memory stores software instructions executable by the at least one processor to perform operations comprising obtaining a location of the at least one drone when the at least one drone is deployed, determining a ground attribute value of a ground surface associated with the location, deriving a payload ratio of a first amount of the first payload relative to a second amount of the second payload based on the ground attribute value, and causing the first payload pod and the second payload pod to release the first amount of the first payload and the second amount of the second payload, respectively, according to the payload ratio. The system may include one or more sensors. The surface attribute value may be determined based on an output from at least one of the one or more sensors. The one or more sensors may include one or more types of sensors selected from the group consisting of GPS sensors, accelerometers, LIDAR sensors, RADAR sensors, cameras, thermometers, magnetometers, gyroscopes, inertial Measurement Units (IMUs), and spectrometers, and/or may include other types of sensors. The one or more sensors may be disposed in the at least one drone. The ground property value may adhere to a ground property namespace or ontology. The ground property value may directly or indirectly quantify one or more properties selected from the group consisting of chemical properties, altitude properties, grade properties, physical properties, optical properties, and geographic properties. The ground property value may be derived at least in part from an image descriptor. The surface attribute values may be determined in real-time from a digital representation of the surface. The surface attribute value may be determined at least in part by referencing a previously characterized attribute of the surface associated with the location. The payload ratio may be derived from the ground property values via one or more selected from the group consisting of a look-up table, a function, and a machine learning model. One or both of the first payload bay and the second payload bay may include a controllable payload opening coupled with the drone controller. At least one of the first and second amounts may include an amount released per unit time, or an amount released per unit area, or another amount. The first and second amounts may be measured by weight. The first and second amounts may be measured by volume. The payload ratio may be in the range of 1:100 to 1:1, or in other ranges as may be practical for a particular use case. One or both of the first payload and the second payload may include a seed. One or both of the first payload and the second payload may comprise spores. One or both of the first payload and the second payload may comprise one or more payloads selected from the group consisting of seeds, spores, fertilizers, pesticides, liquids, modulators, worms, biologicals, powders, slurries, and mycorrhizal fungi. The second payload may include calcium carbonate (e.g., oolitic aragonite, etc.). The location may include one or more selected from the group consisting of a geographic location, a postal code, a geofencing area, a Schneider 2 (S2) unit, a grid location, a fixed location, a relative location, a landmark, a simultaneous localization and mapping (SLAM) location, a visual simultaneous localization and mapping (vSLAM) location, a wireless triangle point,