Stoelen Martin F, de Azambuja Ricardo, López Rodríguez Beatriz, Bonsignorio Fabio, Cangelosi Angelo
Department of Computer Science, Electrical Engineering and Mathematical Sciences, Western Norway University of Applied Sciences, Bergen, Norway.
Fieldwork Robotics Ltd., Cambridge, United Kingdom.
Front Neurorobot. 2022 Mar 11;16:836772. doi: 10.3389/fnbot.2022.836772. eCollection 2022.
Robots used in research on Embodied AI often need to physically explore the world, to fail in the process, and to develop from such experiences. Most research robots are unfortunately too stiff to safely absorb impacts, too expensive to repair if broken repeatedly, and are never operated without the red kill-switch prominently displayed. The GummiArm Project was intended to be an open-source "soft" robot arm with human-inspired tendon actuation, sufficient dexterity for simple manipulation tasks, and with an eye on enabling easy replication of robotics experiments. The arm offers variable-stiffness and damped actuation, which lowers the potential for damage, and which enables new research opportunities in Embodied AI. The arm structure is printable on hobby-grade 3D printers for ease of manufacture, exploits stretchable composite tendons for robustness to impacts, and has a repair-cycle of minutes when something does break. The material cost of the arm is less than $6000, while the full set of structural parts, the ones most likely to break, can be printed with less than $20 worth of plastic filament. All this promotes a concurrent approach to the design of "brain" and "body," and can help increase productivity and reproducibility in Embodied AI research. In this work we describe the motivation for, and the development and application of, this 6 year project.
用于具身人工智能研究的机器人通常需要实际探索世界，在这个过程中遭遇失败，并从这些经历中成长。不幸的是，大多数研究机器人过于僵硬，无法安全地承受冲击；如果反复损坏，维修成本过高；而且在操作时，红色紧急停止开关总是醒目地显示着。GummiArm项目旨在打造一款开源的“软”机器人手臂，它采用受人类启发的肌腱驱动方式，具备足够的灵活性来完成简单的操作任务，并着眼于实现机器人实验的轻松复制。该手臂提供可变刚度和阻尼驱动，降低了损坏的可能性，并为具身人工智能带来了新的研究机会。手臂结构可在业余级3D打印机上打印，便于制造；采用可拉伸复合肌腱，增强了抗冲击能力；当出现故障时，维修周期只需几分钟。该手臂的材料成本不到6000美元，而整套最易损坏的结构部件，用价值不到20美元的塑料丝就能打印出来。所有这些都推动了“大脑”和“身体”设计的并行方法，并有助于提高具身人工智能研究的生产力和可重复性。在这项工作中，我们描述了这个为期6年项目的动机、开发过程及应用情况。
