Automatic Behavior Tree Expansion with LLMs for Robotic Manipulation
Fuente:
arXiv
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866929508103225344 |
|---|---|
| author | Styrud, Jonathan Iovino, Matteo Norrlöf, Mikael Björkman, Mårten Smith, Christian |
| author_facet | Styrud, Jonathan Iovino, Matteo Norrlöf, Mikael Björkman, Mårten Smith, Christian |
| contents | Robotic systems for manipulation tasks are increasingly expected to be easy to configure for new tasks or unpredictable environments, while keeping a transparent policy that is readable and verifiable by humans. We propose the method BEhavior TRee eXPansion with Large Language Models (BETR-XP-LLM) to dynamically and automatically expand and configure Behavior Trees as policies for robot control. The method utilizes an LLM to resolve errors outside the task planner's capabilities, both during planning and execution. We show that the method is able to solve a variety of tasks and failures and permanently update the policy to handle similar problems in the future. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_13356 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Automatic Behavior Tree Expansion with LLMs for Robotic Manipulation Styrud, Jonathan Iovino, Matteo Norrlöf, Mikael Björkman, Mårten Smith, Christian Robotics Robotic systems for manipulation tasks are increasingly expected to be easy to configure for new tasks or unpredictable environments, while keeping a transparent policy that is readable and verifiable by humans. We propose the method BEhavior TRee eXPansion with Large Language Models (BETR-XP-LLM) to dynamically and automatically expand and configure Behavior Trees as policies for robot control. The method utilizes an LLM to resolve errors outside the task planner's capabilities, both during planning and execution. We show that the method is able to solve a variety of tasks and failures and permanently update the policy to handle similar problems in the future. |
| title | Automatic Behavior Tree Expansion with LLMs for Robotic Manipulation |
| topic | Robotics |
| url | https://arxiv.org/abs/2409.13356 |