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AutoMisty: A Multi-Agent LLM Framework for Automated Code Generation in the Misty Social Robot

  • SUNY Buffalo
  • Amrita Vishwa Vidyapeetham

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The social robot's open API allows users to customize open-domain interactions. However, it remains inaccessible to those without programming experience. We introduce AutoMisty, the first LLM-powered multi-agent framework that converts natural-language commands into executable Misty robot code by decomposing high-level instructions, generating sub-task code, and integrating everything into a deployable program. Each agent employs a two-layer optimization mechanism: first, a self-reflective loop that instantly validates and automatically executes the generated code, regenerating whenever errors emerge; second, human review for refinement and final approval, ensuring alignment with user preferences and preventing error propagation. To evaluate AutoMisty's effectiveness, we designed a benchmark task set spanning four levels of complexity and conducted experiments in a real Misty robot environment. Extensive evaluations demonstrate that AutoMisty not only consistently generates high-quality code but also enables precise code control, significantly outperforming direct reasoning with ChatGPT-4o and ChatGPT-o1. All code, optimized APIs, and experimental videos will be publicly released through the webpage: AutoMisty.

Original languageEnglish
Title of host publicationIROS 2025 - 2025 IEEE/RSJ International Conference on Intelligent Robots and Systems, Conference Proceedings
EditorsChristian Laugier, Alessandro Renzaglia, Nikolay Atanasov, Stan Birchfield, Grzegorz Cielniak, Leonardo De Mattos, Laura Fiorini, Philippe Giguere, Kenji Hashimoto, Javier Ibanez-Guzman, Tetsushi Kamegawa, Jinoh Lee, Giuseppe Loianno, Kevin Luck, Hisataka Maruyama, Philippe Martinet, Hadi Moradi, Urbano Nunes, Julien Pettre, Alberto Pretto, Tommaso Ranzani, Arne Ronnau, Silvia Rossi, Elliott Rouse, Fabio Ruggiero, Olivier Simonin, Danwei Wang, Ming Yang, Eiichi Yoshida, Huijing Zhao
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages9194-9201
Number of pages8
ISBN (Electronic)9798331543938
DOIs
StatePublished - 2025
Event2025 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2025 - Hangzhou, China
Duration: Oct 19 2025Oct 25 2025

Publication series

NameIEEE International Conference on Intelligent Robots and Systems
ISSN (Print)2153-0858
ISSN (Electronic)2153-0866

Conference

Conference2025 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2025
Country/TerritoryChina
CityHangzhou
Period10/19/2510/25/25

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