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.
@article{arxiv.2511.20180,
title = {Hibikino-Musashi@Home 2025 Team Description Paper},
author = {Ryohei Kobayashi and Kosei Isomoto and Kosei Yamao and Soma Fumoto and Koshun Arimura and Naoki Yamaguchi and Akinobu Mizutani and Tomoya Shiba and Kouki Kimizuka and Yuta Ohno and Ryo Terashima and Hiromasa Yamaguchi and Tomoaki Fujino and Ryoga Maruno and Wataru Yoshimura and Kazuhito Mine and Tang Phu Thien Nhan and Yuga Yano and Yuichiro Tanaka and Takeshi Nishida and Takashi Morie and Hakaru Tamukoh},
journal= {arXiv preprint arXiv:2511.20180},
year = {2025}
}