RoboGPT : An intelligent agent of making long-horizon decisions for instruction daily tasks

Research output: Contribution to journalArticlepeer-review

Abstract

Robotic agents are tasked with mastering common sense and making long-term sequential decisions to execute daily tasks based on natural language instructions. Recent advancements in Large Language Models (LLMs) have catalyzed efforts for complex robotic planning. However, despite their superior generalization and comprehension capabilities, LLM task plans sometimes suffer from issues of accuracy and feasibility. To address these challenges, we propose RoboGPT \footnote{For more details, please refer to our project page \href{https://github.com/Cwb0106/RoboGPT-}{ https://github.com/Cwb0106/RoboGPT}.
Original languageEnglish
JournalIEEE Transactions on Cognitive and Developmental Systems
Publication statusSubmitted - 2024

Keywords

  • Embodied planning
  • Large language model
  • Embodied AI

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