A Soft Oscillator with On-The-Fly Tunable Dynamics for Adaptive Robotics
Shaoxiang Wang, Tianqi Yue, Hanwen Ge, Hemma Philamore, Andrew Conn
AI summary
Problem
Existing soft pneumatic oscillators suffer from fixed operational parameters and an inherent coupling between input power and output dynamics, limiting their versatility and adaptability in autonomous robotics.
Approach
The authors introduce a multi-port bistable oscillator that continuously reshapes its nonlinear energy landscape via mechanical pre-compression, enabling real-time tuning of oscillation modes and passive adaptation to physical constraints.
Key results
- Decoupled oscillation frequency from output pressure through mechanical pre-compression
- Demonstrated real-time active programming of frequency-amplitude relationships under constant power
- Enabled a soft walker to autonomously switch gaits when navigating confined environments
- Validated a multi-port design generating synchronized oscillating pressure and pulsatile flow outputs
Why it matters
Provides a pathway for electronics-free soft robots to exhibit embodied intelligence and autonomously adapt to unstructured environments.
Abstract
Autonomous and mobile soft robots require in- ternal oscillators, similar to a biological heart, to generate rhythmic motions. However, existing soft oscillators typically have fixed operational parameters and suffer from an inherent coupling between control input and power output, limiting their versatility and adaptability. This paper addresses this challenge by introducing a new design paradigm: a soft, multi-port, bistable oscillator whose core nonlinear energy landscape can be continuously and actively tuned on-the-fly. Our approach, based on mechanically reconfiguring the physical constraints of a bistable elastomeric structure, achieves a decoupling of kinematics (frequency) from dynamics (output pressure). We demonstrate this principle in two modes: first, active program- ming, where we continuously modulate the oscillator’s coupled frequency-amplitude relationship in real-time under a constant power input. Secondly, we demonstrate passive adaptation, where an autonomous walker powered by our oscillator exhibits physical intelligence. By physically interacting with a confined environment, the walker autonomously and instantaneously adapts its gait from a low-frequency, large-amplitude mode to a high-frequency, small-amplitude mode. This work provides a new pathway for creating adaptive, intelligent soft robots that can autonomously respond to their physical world without any electronic computation.