Robot Mission Behavior Trees for Adaptive Task Execution
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Solution Overview
Problem
Existing autonomy systems for robots are limited in extensibility and adaptability, as they are typically configured to address only one aspect of robot operation, hindering the addition of new modules and rapid adaptation to new platforms.
Innovation Solution
A behavior tree-based system that decouples mission planning from execution, allowing for the modeling of tasks and contingency events, enabling autonomous robots to execute maneuvers and adapt to changes through a leaf node library and switch nodes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If existing autonomy systems are configured to address only one aspect of robot operation, then the system design can be simplified and focused, but the extensibility and adaptability of the system deteriorates, limiting the addition of new modules and rapid adaptation to new platforms
Solution Approach 1:
The autonomy system is segmented into distinct behavioral modules organized in a hierarchical tree structure, where each node represents a specific behavior or task. This modular segmentation allows individual behaviors to be developed, tested, and reused independently while maintaining overall system simplicity.
Solution Approach 2:
The behavior tree framework provides a universal structure that can accommodate multiple types of behaviors (navigation, manipulation, sensing, etc.) and can be adapted to different robot platforms. The standardized node interfaces enable the same framework to serve multiple functions across diverse applications.
2Reliability
If existing autonomy systems focus on a narrow mission set with specialized algorithms, then the system can be optimized for specific tasks, but the ability to support new modules and adapt to new platforms deteriorates
Solution Approach 1:
The behavior tree structure enables dynamic reconfiguration of autonomous behaviors through runtime parameter adjustment and node selection. The system can adapt its behavior execution flow dynamically based on environmental conditions and mission requirements while maintaining reliable task completion.
Solution Approach 2:
The system utilizes parameterized behavior nodes that can be configured with specific parameters for different tasks and platforms. By changing parameters rather than rewriting behavior logic, the same behavioral framework can be reliably adapted to new platforms and mission types.
Data Source
AI summary
A method is provided for causing one or more robots to execute a mission. The method includes determining a behavior tree in which the mission is modeled, and causing the one or more robots to execute the mission using the behavior tree and a leaf node library. The behavior tree is expressed as a directed tree of nodes including a switch node, a trigger node representing a selected task, and action nodes representing others of the tasks. The switch node is connected to the trigger node and the action nodes in a parent-child relationship in which the trigger node and the action nodes are children of the switch node. The trigger node is a first of the children that, when ticked by the switch node, returns an identifier of one of the action nodes to trigger the switch node to next tick the one of the action nodes.