Transportation network utilizing multiple autonomous vehicles to transport items between network locations

• US 10,068,486 B1
• Filed: 09/06/2017
• Issued: 09/04/2018
• Est. Priority Date: 06/09/2015
• Status: Active Grant

• Current Assignee: Amazon Technologies, Inc. (Amazon.com, Inc.)
• Original Assignee: Amazon Technologies, Inc. (Amazon.com, Inc.)
• Inventors: Bar-Zeev, Avi, Beckman, Brian C., Buchmueller, Daniel, Dunn, Steven Gregory, Kimchi, Gur
• Primary Examiner(s): Nguyen, Cuong H
• Application Number:
  US15/697,410
• Time in Patent Office: 363 Days
• Field of Search: 701 11, 701 23, 701 25, 701 27, 701 36, 709226, 709245, 709247-248, 709216
• CPC Class Codes: B64C 39/024 of the remote controlled vehicle type, i.e. RPV
• CPC Class Codes: B64U 10/10 Rotorcrafts
• CPC Class Codes: B64U 10/13 Flying platforms
• CPC Class Codes: B64U 10/16 with five or more distinct rotor axes, e.g. octocopters
• CPC Class Codes: B64U 10/25 Fixed-wing aircraft VTOL aircraft B64U10/20
• CPC Class Codes: B64U 20/60 UAVs characterised by the material
• CPC Class Codes: B64U 2101/60 for transporting passengers; for transporting goods other than weapons
• CPC Class Codes: B64U 2101/64 for parcel delivery or retrieval
• CPC Class Codes: B64U 2201/10 autonomous, i.e. by navigating independently from ground or air stations, e.g. by using inertial navigation systems [INS]
• CPC Class Codes: B64U 30/20 Rotors; Rotor supports
• CPC Class Codes: B64U 30/297 Tilting rotors
• CPC Class Codes: B64U 30/299 Rotor guards ducted or shrouded rotors B64U30/26; guards used as ground propulsion B64U60/60
• CPC Class Codes: B64U 50/19 using electrically powered motors
• CPC Class Codes: B64U 50/30 Supply or distribution of electrical power
• CPC Class Codes: B65G 1/0492 with cars adapted to travel in storage aisles
• CPC Class Codes: G01C 21/38 Electronic maps specially adapted for navigation; Updating thereof
• CPC Class Codes: G05D 1/104 involving a plurality of aircrafts, e.g. formation flying traffic control systems for aircraft G08G5/00
• CPC Class Codes: G06Q 10/0832 Special goods or special handling procedures, e.g. handling of hazardous or fragile goods
• CPC Class Codes: G06Q 10/08355 Routing methods
• CPC Class Codes: G08G 5/0013 with a ground station
• CPC Class Codes: G08G 5/0026 : located on the ground
• CPC Class Codes: G08G 5/0034 : Assembly of a flight plan
• CPC Class Codes: G08G 5/0043 : Traffic management of multiple aircrafts from the ground G08G5/003 takes precedence; data processing specially designed for resource management, e.g. scheduling or allocating time, human or machine resources G06Q10/06
• CPC Class Codes: G08G 5/0069 : specially adapted for an unmanned aircraft

Abstract

A transportation network is provided that utilizes autonomous vehicles (e.g., unmanned aerial vehicles) for identifying, acquiring, and transporting items between network locations without requiring human interaction. A travel path for an item through the transportation network may include multiple path segments and corresponding intermediate network locations, with a different autonomous vehicle utilized to transport the item along each path segment. Different possible next network locations for a travel path may selected based on transportation factors such as travel time, cost, safety, etc. (e.g., as may be related to distance, network congestion, inclement weather, etc.). Local processing (e.g., by a control system of an autonomous vehicle) may perform the selection of a next network location for a travel path (e.g., allowing multiple autonomous vehicles to simultaneously engage and depart with items or otherwise travel without having to contact and wait for instructions from centralized system components, etc.).

Claims

1. A system to transport items, the system comprising:

first and second autonomous vehicles configured to transport items between network locations in a transportation network, the first autonomous vehicle comprising;

a propulsion system; and

an autonomous vehicle control system configured to control the propulsion system, the autonomous vehicle control system comprising;

one or more processors; and

a memory coupled to the one or more processors and storing program instructions that when executed by the one or more processors cause the one or more processors to at least;

determine a plurality of different possible next network locations that an item may to be transported to as part of a travel path for the item through the transportation network;

determine, for each of the plurality of different possible next network locations, one or more transportation factors;

select a next network location based on the one or more transportation factors, wherein the selected next network location is an intermediate network location along the travel path for the item for which the transport of the item includes transport along a first path segment to the intermediate network location by the first autonomous vehicle and transport along a second path segment from the intermediate location by the second autonomous vehicle; and

control the propulsion system to transport the item along the first path segment to the intermediate network location so that the second autonomous vehicle is able to further transport the item from the intermediate network location along the second path segment as controlled by an autonomous vehicle control system of the second autonomous vehicle.

2. The system of claim 1, wherein the program instructions when executed by the one or more processors further cause the one or more processors to receive transportation information from the second autonomous vehicle that is utilized to determine at least one of the transportation factors.

3. The system of claim 1, wherein the program instructions when executed by the one or more processors further cause the one or more processors to receive transportation information from the intermediate network location that is utilized to determine at least one of the transportation factors.

4. The system of claim 1, wherein the program instructions when executed by the one or more processors further cause the one or more processors to select the next network location from the plurality of different possible next network locations and to control the propulsion system to transport the item along the first path segment using the local processing of the autonomous vehicle control system without waiting for instructions from a centralized system component.

5. The system of claim 1, wherein the first and second autonomous vehicles are unmanned aerial vehicles.

20. The system of claim 1, wherein the first and second autonomous vehicles primarily utilize ground travel to transport items.

6. An autonomous vehicle configured to transport an item between network locations in a transportation network, the autonomous vehicle comprising:

a propulsion system;

an engagement mechanism to engage an item; and

an autonomous vehicle control system configured to control the propulsion system and the engagement mechanism, the autonomous vehicle control system comprising;

one or more processors; and

a memory coupled to the one or more processors and storing program instructions that when executed by the one or more processors cause the one or more processors to at least;

control the engagement mechanism to engage an item;

determine a next network location to transport the item to based at least in part on one or more transportation factors, wherein the next network location is an intermediate network location from which the item will be further transported by

a second autonomous vehicle;

control the propulsion system to transport the item to the intermediate network location; and

control the engagement mechanism to disengage the item at the intermediate network location so that the second autonomous vehicle may transport the item from the intermediate network location as controlled by an autonomous vehicle control system of the second autonomous vehicle.

14. The autonomous vehicle of claim 6, wherein at least one of the transportation factors is related to an estimated amount of travel cost that would be associated with the autonomous vehicle transporting the item to the intermediate network location.

15. The autonomous vehicle of claim 6, wherein the transportation network includes a plurality of possible next network locations that the item may be transported to and the program instructions when executed by the one or more processors further cause the one or more processors to determine the next network location that the item will be transported to by selecting the next network location from the plurality of possible next network locations based at least in part on the one or more transportation factors.

16. The autonomous vehicle of claim 15, wherein at least one of the transportation factors is related to a level of congestion that is occurring at one of the possible next network locations.

17. The autonomous vehicle of claim 16, wherein the program instructions when executed by the one or more processors further cause the one or more processors to change a previously planned travel path for the item that included the possible next network location where the congestion is occurring to no longer include the possible next network location where the congestion is occurring.

18. The autonomous vehicle of claim 16, wherein the program instructions when executed by the one or more processors further cause the one or more processors to receive transportation information that indicates the level of congestion that is occurring at the possible next network location, and the transportation information is received from at least one of another autonomous vehicle or the possible next network location where the congestion is occurring.

19. The autonomous vehicle of claim 6, wherein at least one of the transportation factors is related to an estimated amount of travel time it would take for the item to be transported to the intermediate network location by the autonomous vehicle.

7. A computer implemented method to transport items, the computer implemented method comprising:

under control of one or more computing systems configured with executable instructions,

determining a plurality of possible next network locations that an item may be transported to as part of a travel path through a transportation network, the travel path beginning at an origin network location and ending at a destination network location for the item, wherein the travel path includes at least two path segments with a different autonomous vehicle utilized to transport the item along each path segment, each of the autonomous vehicles having an autonomous vehicle control system;

receiving transportation information that is related to transport of the item to at least one of the possible next network locations; and

selecting a next network location from the plurality of possible next network locations for the item to be transported to based at least in part on the received transportation information.

8. The computer implemented method of claim 7, wherein the selected next network location is an intermediate network location and the transport of the item includes transport along a first path segment to the intermediate network location by a first autonomous vehicle having a first autonomous vehicle control system and transport along a second path segment from the intermediate location by a second autonomous vehicle having a second autonomous vehicle control system.

9. The computer implemented method of claim 8, wherein the first autonomous vehicle includes the one or more computing systems configured with the executable instructions.

10. The computer implemented method of claim 8, wherein the second autonomous vehicle includes a power module and a charging component that couples to a corresponding charging component at the intermediate network location to provide energy to recharge the power module of the second autonomous vehicle.

11. The computer implemented method of claim 10, further comprising, after selecting the intermediate network location, directing the second autonomous vehicle to travel to the intermediate network location before the item is transported to the intermediate network location and to utilize the charging component of the second autonomous vehicle to recharge the power module in preparation for transporting the item from the intermediate network location.

12. The computer implemented method of claim 7, wherein the selected next network location is a first intermediate network location and the received transportation information indicates that at least one of congestion or inclement weather is occurring at a second intermediate network location that is one of the plurality of possible next network locations, on the basis of which the first intermediate network location is selected over the second intermediate network location.

13. The computer implemented method of claim 7, wherein the selected next network location is a first intermediate network location and the received transportation information indicates that at least one of congestion or inclement weather is not occurring at the first intermediate network location, on the basis of which the first intermediate network location is selected over a second intermediate network location that is one of the plurality of possible next network locations.