Multimodal soft valve enables physical responsiveness for preemptive resilience of soft robots

Author:

Pontin Marco12ORCID,Damian Dana D.123ORCID

Affiliation:

1. Department of Automatic Control and Systems Engineering, University of Sheffield, Sheffield, UK.

2. Sheffield Robotics, University of Sheffield, Sheffield, UK.

3. Insigneo Institute for In Silico Medicine, University of Sheffield, Sheffield, UK.

Abstract

Resilience is crucial for the self-preservation of biological systems: Humans recover from wounds thanks to an immune system that autonomously enacts a multistage response to promote healing. Similar passive mechanisms can enable pneumatic soft robots to overcome common faults such as bursts originating from punctures or overpressurization. Recent technological advancements, ranging from fault-tolerant controllers for robot reconfigurability to self-healing materials, have paved the way for robot resilience. However, these techniques require powerful processors and large datasets or external hardware. How to extend the operational life span of damaged soft robots with minimal computational and physical resources remains unclear. In this study, we demonstrated a multimodal pneumatic soft valve capable of passive resilient reactions, triggered by faults, to prevent or isolate damage in soft robots. In its forward operation mode, the valve, requiring a single supply pressure, isolated punctured soft inflatable elements from the rest of the soft robot in as fast as 21 milliseconds. In its reverse operation mode, the valve can passively protect robots against overpressurization caused by external disturbances, avoiding plastic deformations and bursts. Furthermore, the two modes combined enabled the creation of an endogenously controlled valve capable of autonomous burst isolation. We demonstrated the passive and quick response and the possibility of monolithic integration of the soft valve in grippers and crawling robots. The approach proposed in this study provides a distributed small-footprint alternative to controller-based resilience and is expected to help soft robots achieve uninterrupted long-lasting operation.

Publisher

American Association for the Advancement of Science (AAAS)

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