打造可自适应家庭环境的智能服务机器人，支持个性化任务执行。
Hibikino-Musashi@Home 2025 Team Description Paper
- 用大模型规划任务，调用基础技能完成用户指令
- 构建开源仿真开发环境与机器人视觉训练数据集
- 融合类脑记忆模型实现家庭场景个性化适应
本文介绍Hibikino-Musashi@Home团队为参加国内标准平台联赛所采用的技术。团队开发了用于训练机器人视觉系统的数据集生成器，以及基于人形助手机器人模拟器的开源开发环境。由大语言模型驱动的任务规划器会根据用户请求选择合适的原始技能来执行任务。此外，团队聚焦于类脑记忆模型的研究，以提升系统在不同家庭环境中的适应能力，提供更直观、个性化的辅助。同时，团队还贡献了对RoboCup2024中Pumas团队导航系统的可复用改进。整体目标是设计一款能在家庭中协助人类的智能服务机器人，并通过持续参与竞赛来评估和优化系统性能。
原文摘要 · Abstract (English)
This paper provides an overview of the techniques employed by Hibikino-Musashi@Home, which intends to participate in the domestic standard platform league. The team developed a dataset generator for training a robot vision system and an open-source development environment running on a Human Support Robot simulator. The large-language-model-powered task planner selects appropriate primitive skills to perform the task requested by the user. Moreover, the team has focused on research involving brain-inspired memory models for adaptation to individual home environments. This approach aims to provide intuitive and personalized assistance. Additionally, the team contributed to the reusability of the navigation system developed by Pumas in RoboCup2024. The team aimed to design a home service robot to assist humans in their homes and continuously attend competitions to evaluate and improve the developed system.
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