Safe & Accurate at Speed with Tendons: A Robot Arm for Exploring Dynamic Motion

TL;DR

The paper presents PAMY2, a $4$-DoF tendon-driven robot arm actuated at the base with pneumatic artificial muscles to enable high-speed, safely compliant motion. By combining low moving mass, continuous PTFE Bowden guidance, ball bearings, and passive PAM-based compliance, the design reduces peak collision forces while maintaining control ease and robustness. Extensive experiments confirm improved impact safety, reduced friction, and strong long-term reliability, with a notable table-tennis learning demonstration yielding fast, precise ball returns up to roughly $20$ m/s in real play. The work also contributes open-source hardware, software, and a proprioceptive dataset to facilitate replication and further research in safe, dynamic human-robot collaboration.

Abstract

Operating robots precisely and at high speeds has been a long-standing goal of robotics research. Balancing these competing demands is key to enabling the seamless collaboration of robots and humans and increasing task performance. However, traditional motor-driven systems often fall short in this balancing act. Due to their rigid and often heavy design exacerbated by positioning the motors into the joints, faster motions of such robots transfer high forces at impact. To enable precise and safe dynamic motions, we introduce a four degree-of-freedom~(DoF) tendon-driven robot arm. Tendons allow placing the actuation at the base to reduce the robot's inertia, which we show significantly reduces peak collision forces compared to conventional robots with motors placed near the joints. Pairing our robot with pneumatic muscles allows generating high forces and highly accelerated motions, while benefiting from impact resilience through passive compliance. Since tendons are subject to additional friction and hence prone to wear and tear, we validate the reliability of our robotic arm on various experiments, including long-term dynamic motions. We also demonstrate its ease of control by quantifying the nonlinearities of the system and the performance on a challenging dynamic table tennis task learned from scratch using reinforcement learning. We open-source the entire hardware design, which can be largely 3D printed, the control software, and a proprioceptive dataset of 25 days of diverse robot motions at webdav.tuebingen.mpg.de/pamy2.

Figures (11)

• Figure 1: Visualization of the capabilities of different robot designs. Industrial robots excel in speed, generated forces, and ease of control but are not safe to operate in the proximity of humans. Cobots are easy to control and safe but sacrifice speed and force. Soft robots are generally superior in terms of safety but are hard to control and are often unable to generate high forces. Our robot, PAMY2, is capable of generating high-force and high-velocity trajectories while being significantly safer than most robots. Furthermore, the reduced friction makes our robot easier to control than typical tendon-driven systems.
• Figure 2: Design of the tendon-driven robot arm (a). The arm has a rotational and a swivel DoF within the first (e), (f), and second joint (c), (d). It features ball bearings, which are low in friction. Many parts are self-designed and 3D-printed, which are shown colored in black. The four angle encoders are shown with a small green circuit board. The bowden tubes (b) guide the tendons from the muscles to the joints. They feature an inner tube and outer support elements that help maintain constant tendon length.
• Figure 3: Electrically driven wrist for PAMY2 that can be combined with an end-effector
• Figure 4: Experimental setup for the collision force measurements. A Pilz PRMS is mounted to a table onto which the end effector of the robot is colliding.
• Figure 5: Collision force map depicting peak impact forces resulting from varying impact velocities and contact scenarios for our robot, alongside the Franka Emika Panda and the Universal Robot UR5e for comparison. Our findings reveal that our robot, when operating at high velocities, generates impact forces akin to those exhibited by the other two robots at considerably lower velocities. We express our gratitude to kirschner2021towards for generously sharing the impact data for the Panda and UR5e robot arms.