Design of a Variable Stiffness Quasi-Direct Drive Cable-Actuated Tensegrity Robot
Jonathan Mi, Wenzhe Tong, Yilin Ma, Xiaonan Huang
AI summary
Problem
Tensegrity robots struggle with accurate state estimation and adaptable stiffness due to their high degrees of freedom, unconventional geometry, and severe internal space constraints for sensors and computing.
Approach
The design integrates Quasi-Direct Drive cable actuators with ultra-low-stretch Dyneema cables and motor encoders to precisely estimate cable length and modulate tension. This enables on-the-fly stiffness tuning and accurate proprioception while maintaining a modular exoskeleton for payload and sensor integration.
Key results
- Cable length estimation accuracy under 1% error relative to bar length
- Variable stiffness control achieving up to 7 times minimum stiffness for self-support
- Modular bar and exoskeleton design enabling flexible payload and sensor placement
- Demonstrated load carrying, constrained-space crawling, and collapsed debris lifting
Why it matters
Overcomes critical proprioception and stiffness limitations in tensegrity robotics, providing an open-source platform for autonomous navigation and payload adaptation in unstructured environments.
Abstract
Tensegrity robots excel in tasks requiring extreme levels of deformability and robustness. However, there are chal- lenges in state estimation and payload versatility due to their high number of degrees of freedom and unconventional shape. This paper introduces a modular three-bar tensegrity robot featuring a customizable payload design. Our tensegrity robot employs a novel Quasi-Direct Drive (QDD) cable actuator with low-stretch polymer cables to achieve accurate proprioception without needing external force or torque sensors. The design allows for on-the-fly stiffness tuning for better environment and payload adaptability. In this paper, we present the robot’s design, fabrication, assembly, and experimental results. Experimental data demonstrates the high accuracy cable length estimation (<1% error relative to bar length) and variable stiffness control of the cable actuator up to 7 times the minimum stiffness for self support. The shape morphing and stiffness tuning capabilities are leveraged in two realistic demonstrations. The presented tensegrity robot is a platform for future advancements in au- tonomous operation and open-source module design. Open source design files are available at https://github.com/UMich-HDRLab/ tensegrity-robot-hardware/.