Real-time Puncture Detection and Recovery for Pneumatic Soft Actuators

2026-09-08

AI Summary

研究提出了一种基于单个惯性测量单元的气动软执行器穿刺检测系统，并通过多腔室设计和算法实现故障恢复，提高软机器人系统的可靠性和安全性。

Abstract

Soft robots offer safe and adaptive interaction with humans and unstructured environments through their inherent ability to deform and comply. Pneumatic actuators are one way to build soft robots. They are typically made from soft silicone materials and are especially effective for driving such systems, enabling smooth and adaptable motion. However, their compliant nature also makes them vulnerable to mechanical failures like punctures and tears, limiting practical deployment. To address this, we propose a puncture detection system for soft actuators using motion data from a single inertial measurement unit. Extracted features are used to train anomaly detectors for puncture detection and non-linear models to estimate severity. We also introduce a multi-chamber pneumatic soft bending actuator capable of diverse configurations via selective chamber inflation. Our algorithm identifies the punctured chamber and provides a severity score using a chamber perturbation scheme. Anomaly detectors are trained on normal operation data and detect damage through reconstruction errors, while severity is estimated by a separate model trained under slightly modified conditions. Finally, we demonstrate a failure recovery strategy to maintain actuation force post-failure. This approach enhances the reliability and safety of soft robotic systems through real-time, data-driven damage detection.

Problem

• puncture detection
• soft actuators
• mechanical failures
• real-time
• failure recovery

Innovation

• puncture detection
• inertial measurement unit
• anomaly detectors
• multi-chamber actuator
• failure recovery