Hibikino-Musashi@Home 2026 チーム記述論文
Hibikino-Musashi@Home 2026 Team Description Paper
RoboCup@Home 2026 オープンプラットフォームリーグ向けに、学習ベースの物体認識、RoomPlanによる意味地図生成、LLMプランナ、FPGA実装のリザバー計算による行動認識などを統合したサービスロボットシステムを紹介する論文。
著者: Soma Fumoto, Ryohei Kobayashi, Taiki Watanabe, Yuga Yano, Akinobu Mizutani, Naoki Yamaguchi, Ryo Terashima, Ryusei Sakakibara, Kazuma Futami, Keita Okumura, Kosei Isomoto, Koshun Arimura, Yuta Ohno, Tomoaki Fujino, Sojiro Shimada, Yuichiro Tanaka, Takeshi Nishida, Hakaru Tamukoh
分類: cs.RO
原文アブストラクト
This paper presents an overview of the integrated technologies developed for the Open Platform League at RoboCup@Home 2026 in Incheon. A vision system integrated with learning-based, training-free models enables robust object recognition for both known and unknown objects. We introduce a RoomPlan-based method that semi-automatically registers furniture geometry and labels to generate semantic maps. Additionally, a large language model-based planner interprets the instructions recognized by Whisper and generates primitive skill sequences for execution. A reservoir-computing framework serves as a lightweight temporal-processing model for action recognition. Its field-programmable gate array-based implementation enables low-power, real-time operation. This is key to removing operational time constraints for service robots. Open-source releases, including task environments, dataset tools, and navigation frameworks, enhance reproducibility, reuse, and continuous progress within the RoboCup@Home community.