Task execution engine and system

Patent metadata

Field	Value
Publication number	US-2020210960-A1
Application number	US-201816232983-A
Country	US
Kind code	A1
Filing date	Dec 26, 2018
Priority date	Dec 26, 2018
Publication date	Jul 2, 2020
Grant date	—

Abstract

Methods are disclosed for optimizing execution of tasks for users. A processing system including a processor detects a triggering condition for a transport task for transporting a subject from a first location to a second location via usage of an autonomous vehicle, establishes a negotiated task coordination plan between a user and a third party provider for performing the transport task, and executes the negotiated task coordination plan, wherein the executing causes the autonomous vehicle to travel between the first location and the second location for transporting the subject.

First claim

What is claimed is:

1 . A method comprising:
detecting, by a processing system comprising at least one processor, a triggering condition for a transport task for transporting a subject from a first location to a second location via usage of an autonomous vehicle; establishing, by the processing system, a negotiated task coordination plan between a user and a third party provider for performing the transport task; and executing, by the processing system, the negotiated task coordination plan, wherein the executing causes the autonomous vehicle to travel between the first location and the second location for transporting the subject.

2 . The method of claim 1 , further comprising:
receiving, by the processing system, feedback from the user.

3 . The method of claim 1 , further comprising:
receiving, by the processing system, feedback from the third party provider.

4 . The method of claim 1 , wherein the processing system employs a machine learning algorithm.

5 . The method of claim 1 , wherein the autonomous vehicle comprises an autonomous motor vehicle, an autonomous ship, or an autonomous drone.

6 . The method of claim 1 , wherein the processing system is granted a consent by the user to access task data for establishing the negotiated task coordination plan.

7 . The method of claim 6 , wherein the processing system is further granted a consent by the user to store the task data to be accessible by the third party provider.

8 . The method of claim 1 , further comprising:
creating a task template for a plurality of tasks with a plurality of triggering conditions, wherein the transport task is one of the plurality of tasks and the triggering condition is one of the plurality of triggering conditions.

9 . The method of claim 1 , wherein the establishing the negotiated task coordination plan comprises:
receiving a task coordination plan from the user; forwarding the task coordination plan to the third party provider; and receiving the negotiated task coordination plan from the third party provider, wherein negotiated task coordination plan comprises the task coordination plan with at least one modification.

10 . A non-transitory computer-readable medium storing instructions which, when executed by a processing system including at least one processor, cause the processing system to perform operations, the operations comprising:
detecting a triggering condition for a transport task for transporting a subject from a first location to a second location via usage of an autonomous vehicle; establishing a negotiated task coordination plan between a user and a third party provider for performing the transport task; and executing the negotiated task coordination plan, wherein the executing causes the autonomous vehicle to travel between the first location and the second location for transporting the subject.

11 . The non-transitory computer-readable medium of claim 10 , the operations further comprising:
receiving feedback from the user.

12 . The non-transitory computer-readable medium of claim 10 , the operations further comprising: receiving feedback from the third party provider.

13 . The non-transitory computer-readable medium of claim 10 , wherein the processing system employs a machine learning algorithm.

14 . The non-transitory computer-readable medium of claim 10 , wherein the autonomous vehicle comprises an autonomous motor vehicle, an autonomous ship, or an autonomous drone.

15 . The non-transitory computer-readable medium of claim 10 , wherein the processing system is granted a consent by the user to access task data for establishing the negotiated task coordination plan.

16 . The non-transitory computer-readable medium of claim 15 , wherein the processing system is further granted a consent by the user to store the task data to be accessible by the third party provider.

17 . The non-transitory computer-readable medium of claim 10 , the operations further comprising:
creating a task template for a plurality of tasks with a plurality of triggering conditions, wherein the transport task is one of the plurality of tasks and the triggering condition is one of the plurality of triggering conditions.

18 . The non-transitory computer-readable medium of claim 10 , wherein the establishing the negotiated task coordination plan comprises:
receiving a task coordination plan from the user; forwarding the task coordination plan to the third party provider; and receiving the negotiated task coordination plan from the third party provider, wherein negotiated task coordination plan comprises the task coordination plan with at least one modification.

19 . A device comprising:
a processing system including at least one processor; and a computer-readable medium storing instructions which, when executed by the processing system, cause the processing system to perform operations, the operations comprising:
detecting a triggering condition for a transport task for transporting a subject from a first location to a second location via usage of an autonomous vehicle;
establishing a negotiated task coordination plan between a user and a third party provider for performing the transport task; and
executing the negotiated task coordination plan, wherein the executing causes the autonomous vehicle to travel between the first location and the second location for transporting the subject.

20 . The device of claim 19 , wherein the processing system employs a machine learning algorithm.

Assignees

• At & T Ip I Lp

Inventors

• Soryal Joseph
• Jaoude Naila
• Serban Cristina
• Rao Lalita V
• Hansen Tony

Classifications

• G06N20/00

  Machine learning · CPC title

• G01C21/3484

  Personalized, e.g. from learned user behaviour or user-defined profiles · CPC title

• G01C21/343

  Calculating itineraries (travelling salesman problem G06Q10/04; optimisation of routes G06Q10/047) · CPC title

• G06Q10/1097 Primary

  using calendar-based scheduling for task assignment · CPC title

• G06F9/48

  Program initiating; Program switching, e.g. by interrupt · CPC title