Mission Controller Framework for Multi-Agent Robot Task Coordination
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Traditional robotic systems struggle with scalability and coordination in complex environments, particularly when multiple task agents are involved, and existing behavior trees are agent-centric, failing to holistically manage interactions between agents.
Innovation Solution
A mission controller generates a behavior-based mission framework that breaks down tasks into synchronized sequences, incorporating behavior models for multiple task agents, including autonomous mobile systems, specialized agents, and non-operative items, with synchronization points to coordinate actions and account for interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional agent-centric behavior trees are used to control autonomous machines, then individual agent autonomy is maintained, but coordination and holistic management of interactions between multiple agents deteriorates
Solution Approach 1:
The patent introduces a mission controller as an intermediary component that receives high-level mission commands and decomposes them into coordinated task sequences for multiple agents. This mediator handles the coordination complexity centrally while allowing individual agents to maintain their autonomy in executing specific tasks, thus resolving the contradiction between agent independence and system-wide coordination.
Solution Approach 2:
The mission framework is segmented into hierarchical levels: high-level mission objectives, mid-level task sequences, and low-level individual agent actions. This segmentation allows the system to manage coordination at the mission controller level while preserving agent autonomy at the execution level, effectively addressing the complexity issue without sacrificing adaptability.
2Productivity
If multiple task agents are deployed to perform complex missions, then task distribution and parallel execution are improved, but coordination and synchronization between agents deteriorates
Solution Approach 1:
The mission controller performs preliminary decomposition of missions into coordinated task sequences before execution, establishing synchronization points and coordination protocols in advance. This preliminary planning ensures that multiple agents can execute tasks in parallel while maintaining reliable coordination, as the interaction framework is predetermined and validated before deployment.
3Manufacturing precision
If behavior models are customized for each specific mission, then task execution precision is improved, but system complexity and configuration time deteriorates
Solution Approach 1:
The system uses parameterized behavior models that can be customized for specific missions by changing configuration parameters rather than creating entirely new models. This allows precise task execution for different mission types while maintaining a reusable core framework, thereby reducing configuration complexity and time.
4Device complexity
If centralized mission control is implemented, then holistic coordination is improved, but system scalability and flexibility deteriorates
Solution Approach 1:
The system adds a temporal and hierarchical dimension to coordination by organizing tasks into sequences with synchronization points, rather than attempting to coordinate all agents simultaneously at the same level. This dimensional approach allows centralized control to manage complexity effectively while preserving scalability, as agents can be added to existing sequences without redesigning the entire coordination framework.
Data Source
AI summary
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.