인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록·키워드
This paper proposes ChainBot, an agent system that autonomously plans and executes robotic object manipulation tasks based on a user's natural language instructions by dynamically chaining multiple foundation models. The ChainBot system uses a large language model (LLM) for effective task planning. To ensure the generation of correct task plans, the system enriches the LLM prompt with useful context, including plan examples and domain-specific heuristic knowledge. Before execution, ChainBot also uses a secondary LLM for pre-execution validation. If an error is detected, the system replans the task using the validation result as feedback. During task execution, ChainBot employs a large multimodal model (LMM) to monitor the process for quick error discovery and recovery. This is achieved by checking both the preconditions and postconditions of each action using real-time camera images captured before and after execution. As a result, ChainBot achieves fully autonomous robotic manipulation without user intervention when implemented as an agent system using the LangChain and LangGraph frameworks. Through various quantitative and qualitative experiments, this paper demonstrates the superiority of ChainBot compared to conventional systems.
본문·목차
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
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UCI(KEPA) : I410-151-26-02-096088858