MEVION: Low-Cost Open-Source Data Collection System for Powerful and High-Speed Dual-Arm Manipulation
2026-07-20 • Robotics
Robotics
AI summaryⓘ
The authors created MEVION, a more powerful and still low-cost robot with four arms that can move faster and lift heavier things than a popular older robot called ALOHA. MEVION is built mostly from easy-to-get parts and uses a smart joint design that helps it be stronger without getting too heavy. They show that MEVION can do tasks that ALOHA couldn't, like faster or tougher object handling, and can help teach robots by watching demonstrations. They shared all their designs and software online for others to use.
dual-arm robotrobotic foundation models6-DoF (degrees of freedom)torqueobject manipulationimitation learningclosed-link mechanismsheet metal weldingopen-source hardwarerobot data collection
Authors
Kento Kawaharazuka, Yoshiki Obinata, Hirokazu Ishida, Jihoon Oh, Temma Suzuki, Shintaro Inoue, Keita Yoneda, Ayumu Iwata, Kei Okada
Abstract
The global competition for developing robotic foundation models is intensifying. Among the data collection systems used for dual-arm robots, ALOHA is representative of being low-cost and open-source, and is widely adopted by researchers as a de facto standard. However, due to its limited ability to generate high forces and speeds, it is difficult to handle heavy objects or perform fast manipulations. To address this, we developed MEVION, a low-cost and open-source dual-arm robot data collection system capable of generating greater force and speed. All parts of this robot can be sourced through e-commerce, and by extensively utilizing sheet metal welding, its large body structure is constructed with a small number of components at low cost, while also simplifying assembly. MEVION is equipped with four 6-DoF arms with parallel grippers. Each arm weighs 7.0 kg and has a maximum torque of 60 Nm, and the entire system can be constructed for about USD 14,000. The elbow joint adopts a closed-link mechanism similar to those used in quadruped robots, which reduces the distal mass and enables higher force and speed output at the end-effector. We demonstrate that MEVION enables data collection for object manipulation tasks not previously possible and supports imitation learning-based motion generation. All hardware and software of this work are included in the Supplementary Materials or https://github.com/haraduka/mevion.