Hibikino-Musashi@Home 2025 Team Description Paper

Fuente: arXiv
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Dettagli Bibliografici
Autori principali: Kobayashi, Ryohei, Isomoto, Kosei, Yamao, Kosei, Fumoto, Soma, Arimura, Koshun, Yamaguchi, Naoki, Mizutani, Akinobu, Shiba, Tomoya, Kimizuka, Kouki, Ohno, Yuta, Terashima, Ryo, Yamaguchi, Hiromasa, Fujino, Tomoaki, Maruno, Ryoga, Yoshimura, Wataru, Mine, Kazuhito, Nhan, Tang Phu Thien, Yano, Yuga, Tanaka, Yuichiro, Nishida, Takeshi, Morie, Takashi, Tamukoh, Hakaru
Natura: Preprint
Pubblicazione: 2025
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author Kobayashi, Ryohei
Isomoto, Kosei
Yamao, Kosei
Fumoto, Soma
Arimura, Koshun
Yamaguchi, Naoki
Mizutani, Akinobu
Shiba, Tomoya
Kimizuka, Kouki
Ohno, Yuta
Terashima, Ryo
Yamaguchi, Hiromasa
Fujino, Tomoaki
Maruno, Ryoga
Yoshimura, Wataru
Mine, Kazuhito
Nhan, Tang Phu Thien
Yano, Yuga
Tanaka, Yuichiro
Nishida, Takeshi
Morie, Takashi
Tamukoh, Hakaru
author_facet Kobayashi, Ryohei
Isomoto, Kosei
Yamao, Kosei
Fumoto, Soma
Arimura, Koshun
Yamaguchi, Naoki
Mizutani, Akinobu
Shiba, Tomoya
Kimizuka, Kouki
Ohno, Yuta
Terashima, Ryo
Yamaguchi, Hiromasa
Fujino, Tomoaki
Maruno, Ryoga
Yoshimura, Wataru
Mine, Kazuhito
Nhan, Tang Phu Thien
Yano, Yuga
Tanaka, Yuichiro
Nishida, Takeshi
Morie, Takashi
Tamukoh, Hakaru
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2511_20180
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Hibikino-Musashi@Home 2025 Team Description Paper
Kobayashi, Ryohei
Isomoto, Kosei
Yamao, Kosei
Fumoto, Soma
Arimura, Koshun
Yamaguchi, Naoki
Mizutani, Akinobu
Shiba, Tomoya
Kimizuka, Kouki
Ohno, Yuta
Terashima, Ryo
Yamaguchi, Hiromasa
Fujino, Tomoaki
Maruno, Ryoga
Yoshimura, Wataru
Mine, Kazuhito
Nhan, Tang Phu Thien
Yano, Yuga
Tanaka, Yuichiro
Nishida, Takeshi
Morie, Takashi
Tamukoh, Hakaru
Robotics
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.
title Hibikino-Musashi@Home 2025 Team Description Paper
topic Robotics
url https://arxiv.org/abs/2511.20180