Bridging hard and soft: Mechanical metamaterials enable rigid torque transmission in soft robots

扭矩 软机器人 机器人 机器人学 运动学 机械臂 计算机科学 机械工程 模拟 物理 工程类 人工智能 经典力学 热力学
作者
Michel Carton,Jakub F. Kowalewski,Jiani Guo,Jacob F. Alpert,Aman Garg,Daniel Revier,Jeffrey Lipton
出处
期刊:Science robotics [American Association for the Advancement of Science]
卷期号:10 (100): eads0548-eads0548 被引量:27
标识
DOI:10.1126/scirobotics.ads0548
摘要

Torque and continuous rotation are fundamental methods of actuation and manipulation in rigid robots. Soft robot arms use soft materials and structures to mimic the passive compliance of biological arms that bend and extend. This use of compliance prevents soft arms from continuously transmitting and exerting torques to interact with their environment. Here, we show how relying on patterning structures instead of inherent material properties allows soft robotic arms to remain compliant while continuously transmitting torque to their environment. We demonstrate a soft robotic arm made from a pair of mechanical metamaterials that act as compliant constant-velocity joints. The joints are up to 52 times stiffer in torsion than bending and can bend up to 45°. This robot arm continuously transmits torque while remaining flexible in all other directions. The arm's mechanical design achieves high motion repeatability (0.4 millimeters and 0.1°) when tracking trajectories. We then trained a neural network to learn the inverse kinematics, enabling us to program the arm to complete tasks that are challenging for existing soft robots, such as installing light bulbs, fastening bolts, and turning valves. The arm's passive compliance makes it safe around humans and provides a source of mechanical intelligence, enabling it to adapt to misalignment when manipulating objects. This work will bridge the gap between hard and soft robotics with applications in human assistance, warehouse automation, and extreme environments.
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