Task management for robotic systems and applications
In various examples, behavior-based mission task management for mobile autonomous machine systems and applications are provided. A mission controller may generate a mission behavior model logic framework for a mission that accounts for the actions of a set of multiple task agents that play a role in completing the mission. The mission controller may assemble a framework starting from a baseline task sequence, correlate tasks defined by the baseline task sequence with pre-defined behavior models, and customize those behavior models based on mission task customization parameters. The mission controller may provide the mission behavior model logic framework to a mission dispatch function. Individual autonomous mobile task agents may then proceed to execute their assigned portions of local task sequences in accordance with the customized behavior models distributed to them by the mission dispatch function.
1 . A system comprising:
one or more processing units to:
receive a mission request indicating a primary task;
correlate the primary task with a baseline task sequence;
assemble a behavior model logic framework that defines a plurality of local tasks performed by a plurality of task agents based on the baseline task sequence, the plurality of local tasks comprising one or more pre-defined modular behavior models, the behavior model logic framework comprising a holistic representation of individual task agents of the plurality of task agents and their respective local tasks involved in completing the primary task;
augment the one or more pre-defined modular behavior models within the behavior model logic framework based at least on one or more task customization parameters; and
control an operation of at least one task agent of the plurality of task agents based at least on a distribution of one or more segments of the behavior model logic framework for at least one mobile autonomous machine agent of the plurality of task agents to execute one or more tasks of the plurality of local tasks.
2 . The system of claim 1 , wherein the one or more processing units are further to:
distribute a first segment of the one or more segments of the behavior model logic framework to a first mobile autonomous machine agent to execute a first set of the one or more tasks of the plurality of local tasks; and
distribute a second segment of the one or more segments of the behavior model logic framework to a second mobile autonomous machine agent to execute a second set of the one or more tasks of the plurality of local tasks.
3 . The system of claim 1 , wherein the one or more processing units are further to:
execute a proxy representation that simulates execution of a first behavior model of the one or more pre-defined modular behavior models to represent an estimated state of a first task agent of the plurality of task agents that does not receive the first behavior model.
4 . The system of claim 3 , wherein the one or more processing units are further to:
operate the first task agent based on the first behavior model using commands communicated to an application programming interface (API).
5 . The system of claim 1 , wherein the one or more processing units are further to:
transmit the one or more segments of the behavior model logic framework to a dispatch function to distribute the one or more segments of the behavior model logic framework for the at least one mobile autonomous machine agent, wherein the dispatch function communicates with the at least one mobile autonomous machine agent via a wireless communication link.
6 . The system of claim 1 , wherein the one or more processing units are further to:
augment the one or more pre-defined modular behavior models based on at least one navigation route for the at least one mobile autonomous machine agent derived based at least on the mission request.
7 . The system of claim 1 , wherein the one or more processing units are further to:
determine the one or more task customization parameters based at least on a facility map to augment the one or more pre-defined modular behavior models.
8 . The system of claim 1 , wherein the one or more segments of the behavior model logic framework comprises at least one modular behavior model that instructs the at least one mobile autonomous machine agent to synchronize an action with at least one other task agent of the plurality of task agents to execute the one or more tasks of the plurality of local tasks.
9 . The system of claim 1 , wherein at least a first behavior model of the one or more pre-defined modular behavior models comprises a behavior tree that includes logic to control switching between sequences of behaviors.
10 . The system of claim 1 , wherein the one or more processing units are further to:
assign an identifier to the behavior model logic framework; and
track a status of the plurality of task agents based at least on the identifier.
11 . The system of claim 1 , wherein the one or more processing units are further to:
update the behavior model logic framework based on feedback data from one or more of the plurality of task agents to generate an updated segment of the behavior model logic framework; and
distribute the updated segment of the behavior model logic framework for the at least one mobile autonomous machine agent of the plurality of task agents.
12 . The system of claim 1 , wherein the one or more processing units are comprised in at least one of:
a control system for an autonomous or semi-autonomous machine;
a perception system for an autonomous or semi-autonomous machine;
a system for performing simulation operations;
a system for performing digital twin operations;
a system for performing light transport simulation;
a system for performing collaborative content creation for three-dimensional assets;
a system for generating or presenting at least one of virtual reality content, augmented reality content, or mixed reality content;
a system for performing deep learning operations;
a system for performing real-time streaming;
a system implemented using an edge device;
a system implemented using a robot;
a system for performing conversational AI operations;
a system for generating synthetic data;
a system incorporating one or more virtual machines (VMs);
a system implemented at least partially in a data center;
a system for performing generative AI operations;
a system implemented at least partially using a language model; or
a system implemented at least partially using cloud computing resources.
13 . A processor comprising:
one or more processing units to:
correlate a baseline task sequence with one or more pre-defined modular behavior models, the baseline task sequence derived from a mission request;
augment the one or more pre-defined modular behavior models based at least on one or more task customization parameters to generate one or more custom behavior models;
assemble a behavior model logic framework that defines a sequence of a plurality of local tasks performed by a plurality of task agents based on the baseline task sequence and the one or more custom behavior models, the behavior model logic framework comprising a holistic representation of individual task agents of the plurality of task agents and their respective local tasks involved in completing the primary task; and
operate at least one mobile autonomous machine agent of the plurality of task agents to perform at least one local task of the plurality of local tasks by distributing at least a segment of the behavior model logic framework to the at least one mobile autonomous machine agent.
14 . The processor of claim 13 , wherein the one or more processing units are further to:
execute a proxy representation that simulates execution of a first custom behavior model of the one or more custom behavior models to represent an estimated state of a first task agent of the plurality of task agents that does not receive the first custom behavior model.
15 . The processor of claim 14 , wherein the one or more processing units are further to:
operate the first task agent based on the first custom behavior model using commands communicated to an application programming interface (API).
16 . The processor of claim 13 , wherein the one or more processing units are further to:
compute at least one navigation route for the at least one mobile autonomous machine agent derived based at least on the mission request; and
augment the one or more pre-defined modular behavior models based on the at least one navigation route.
17 . The processor of claim 13 , wherein the segment of the behavior model logic framework comprises at least one modular behavior model that instructs the at least one mobile autonomous machine agent to synchronize an action with at least one other task agent of the plurality of task agents.
18 . The processor of claim 13 , wherein the one or more processing units are further to:
update the behavior model logic framework based on feedback data from one or more of the plurality of task agents to generate an updated segment of the behavior model logic framework; and
distribute the updated segment of the behavior model logic framework for the at least one mobile autonomous machine agent of the plurality of task agents to execute one or more tasks of the plurality of local tasks.
19 . The processor of claim 13 , wherein the one or more processing units are comprised in at least one of:
a control system for an autonomous or semi-autonomous machine;
a perception system for an autonomous or semi-autonomous machine;
a system for performing simulation operations;
a system for performing digital twin operations;
a system for performing light transport simulation;
a system for performing collaborative content creation for three-dimensional assets;
a system for generating or presenting at least one of virtual reality content, augmented reality content, or mixed reality content;
a system for performing deep learning operations;
a system for performing real-time streaming;
a system implemented using an edge device;
a system implemented using a robot;
a system for performing conversational AI operations;
a system for generating synthetic data;
a system incorporating one or more virtual machines (VMs);
a system implemented at least partially in a data center;
a system for performing generative AI operations;
a system implemented at least partially using a language model; or
a system implemented at least partially using cloud computing resources.
20 . A method comprising:
assembling a sequence of behavior models to generate a behavior model logic framework that defines a sequence of a plurality of local tasks performed by a plurality of task agents, and controlling an operation of at least one mobile autonomous machine agent of the plurality of task agents by distributing at least a segment of the behavior model logic framework to the at least one mobile autonomous machine agent, the behavior model logic framework comprising a holistic representation of individual task agents of the plurality of task agents and their respective local tasks involved in completing the primary task.