MEVIUS2: 板金溶接とマルチモーダル知覚を備えた実用的なオープンソース四足ロボット
MEVIUS2: Practical Open-Source Quadruped Robot with Sheet Metal Welding and Multimodal Perception
Boston DynamicsのSpotと同等のサイズで、板金溶接と金属加工により耐久性の高い構造を実現し、LiDARや高ダイナミックレンジカメラを搭載したオープンソース四足ロボットを開発した。
詳しい要約
1. どんなもの？
2. 先行研究と比べてどこがすごい？
3. 技術・手法の肝は？
4. どうやって有効だと検証した？
5. 議論はある？
6. 次に読むべき論文は？
※ AIが要旨から生成した要約です。正確性は原文をご確認ください。
著者: Kento Kawaharazuka, Keita Yoneda, Shintaro Inoue, Temma Suzuki, Jun Oda, Kei Okada
分類: cs.RO
原文アブストラクト
Various quadruped robots have been developed to date, and thanks to reinforcement learning, they are now capable of traversing diverse types of rough terrain. In parallel, there is a growing trend of releasing these robot designs as open-source, enabling researchers to freely build and modify robots themselves. However, most existing open-source quadruped robots have been designed with 3D printing in mind, resulting in structurally fragile systems that do not scale well in size, leading to the construction of relatively small robots. Although a few open-source quadruped robots constructed with metal components exist, they still tend to be small in size and lack multimodal sensors for perception, making them less practical. In this study, we developed MEVIUS2, an open-source quadruped robot with a size comparable to Boston Dynamics' Spot, whose structural components can all be ordered through e-commerce services. By leveraging sheet metal welding and metal machining, we achieved a large, highly durable body structure while reducing the number of individual parts. Furthermore, by integrating sensors such as LiDARs and a high dynamic range camera, the robot is capable of detailed perception of its surroundings, making it more practical than previous open-source quadruped robots. We experimentally validated that MEVIUS2 can traverse various types of rough terrain and demonstrated its environmental perception capabilities. All hardware, software, and training environments can be obtained from Supplementary Materials or https://github.com/haraduka/mevius2.
