arXiv:2611.16297 · v1

Hibikino-Musashi@Home 2026 Team Description Paper

首次提交 2026-11-12 12:54

版本更新 2026-11-12 12:54

雷达观测 2026-11-13 14:16

摘要

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.