ReefFlex: A Generative Design Framework for Soft Robotic Grasping of Organic and Fragile objects
Josh Pinskier, Sarah Baldwin, Stephen Rodan, David Howard

TL;DR
ReefFlex is a novel generative design framework for soft robotic fingers that enhances the safe grasping and manipulation of fragile coral, supporting reef restoration efforts through optimized, adaptable soft end-effectors.
Contribution
It introduces a generative, multi-objective optimization approach for designing soft robotic fingers tailored for fragile, heterogeneous objects like coral, enabling safer and more effective reef rehabilitation.
Findings
ReefFlex improves grasp success rates on fragile coral objects.
The method reduces disturbance and increases positioning accuracy during coral handling.
ReefFlex outperforms traditional designs in complex, cluttered environments.
Abstract
Climate change, invasive species and human activities are currently damaging the world's coral reefs at unprecedented rates, threatening their vast biodiversity and fisheries, and reducing coastal protection. Solving this vast challenge requires scalable coral regeneration technologies that can breed climate-resilient species and accelerate the natural regrowth processes; actions that are impeded by the absence of safe and robust tools to handle the fragile coral. We investigate ReefFlex, a generative soft finger design methodology that explores a diverse space of soft fingers to produce a set of candidates capable of safely grasping fragile and geometrically heterogeneous coral in a cluttered environment. Our key insight is encoding heterogeneous grasping into a reduced set of motion primitives, creating a simplified, tractable multi-objective optimisation problem. To evaluate the…
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Taxonomy
TopicsSoft Robotics and Applications · Micro and Nano Robotics · Robot Manipulation and Learning
