Robot Behavior Tree Planning for Lower-Complexity Task Execution
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Solution Overview
Problem
Current behavior tree implementations for robot control are complex, labor-intensive, and prone to errors due to repeated subtrees, high computational costs, and inefficiencies in traversing and data transfer, making them unsuitable for efficient and error-free operation in dynamic environments.
Innovation Solution
A method using a behavior tree with modular, hierarchical structure that includes a planner section to dynamically adjust the execution of sub-trees based on environmental and task-specific conditions, allowing for parallel and sequential execution of actions, and optimizing tick frequency to balance efficiency and responsiveness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If behavior trees are used for robot control with repeated subtrees, then complex tasks can be structured modularly, but complexity and computational cost increase
Solution Approach 1:
The behavior tree is segmented into distinct functional blocks (sequence blocks, parallel blocks, selector blocks) that can be independently defined and reused. Each block type encapsulates specific control logic, allowing the overall behavior tree to be divided into manageable segments that reduce complexity while maintaining modular task structuring capability.
Solution Approach 2:
Functional blocks within the behavior tree can be copied and reused multiple times across different parts of the tree. Instead of defining the same subtree repeatedly, a single functional block definition can be instantiated multiple times with different parameters, reducing the overall complexity and computational cost of the behavior tree while maintaining adaptability.
2Extent of automation
If behavior trees are used for robot control, then autonomous decision-making is enabled, but labor intensity and error probability increase
Solution Approach 1:
The behavior tree system enables autonomous decision-making where the robot independently evaluates conditions and executes appropriate actions without continuous human intervention. The system serves itself by automatically navigating, manipulating objects, and adapting to environmental changes based on the structured behavior tree logic, reducing the need for manual control while maintaining manageable programming effort through standardized block structures.
3Speed
If high tick frequency is used for behavior tree traversal, then responsiveness is improved, but computational efficiency decreases
Solution Approach 1:
The behavior tree traversal operates at periodic tick intervals rather than continuously. By configuring the tick frequency appropriately, the system achieves a balance between responsiveness (sufficiently high frequency to respond to environmental changes) and computational efficiency (low enough frequency to avoid unnecessary processing). This periodic execution allows the robot to maintain awareness of its state and environment without wasting computational resources on excessive traversals.
Data Source
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AI summary
Disclosed is a method and a system for controlling an apparatus, by using a behavior tree for an assigned task performed by the apparatus, wherein the behavior tree comprises a planner section and an activation section, wherein the method comprises calling a planner section, determining the state of the apparatus and setting an activation status by a planner section in response to being called, and evaluating the activation status before executing the assigned task