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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 tackles the challenge of safely handling fragile and geometrically diverse corals by introducing a hierarchical generative design framework that combines diversity-based topology optimization with multi-load grasping concepts. The method uses SIMP-based topology optimization across passive and active finger formulations, producing a library of high-quality, diverse soft fingers that are subsequently validated in simulation and real hardware. A novel cam-barrel end-effector mechanically orchestrates finger motion, enabling reliable grasping in cluttered aquaculture environments, with experimental validation showing improved grasp quality and robustness relative to conventional Fin Ray designs. The results demonstrate practical impact for scalable coral farming and provide a generalizable approach for designing soft end-effectors for delicate, cluttered handling tasks in robotics.

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 method, we design a soft robot for reef rehabilitation, which grows and manipulates coral in onshore aquaculture facilities for future reef out-planting. We demonstrate ReefFlex increases both grasp success and grasp quality (disturbance resistance, positioning accuracy) and reduces in adverse events encountered during coral manipulation compared to reference designs. ReefFlex, offers a generalisable method to design soft end-effectors for complex handling and paves a pathway towards automation in previously unachievable domains like coral handling for restoration.

ReefFlex: A Generative Design Framework for Soft Robotic Grasping of Organic and Fragile objects

TL;DR

ReefFlex tackles the challenge of safely handling fragile and geometrically diverse corals by introducing a hierarchical generative design framework that combines diversity-based topology optimization with multi-load grasping concepts. The method uses SIMP-based topology optimization across passive and active finger formulations, producing a library of high-quality, diverse soft fingers that are subsequently validated in simulation and real hardware. A novel cam-barrel end-effector mechanically orchestrates finger motion, enabling reliable grasping in cluttered aquaculture environments, with experimental validation showing improved grasp quality and robustness relative to conventional Fin Ray designs. The results demonstrate practical impact for scalable coral farming and provide a generalizable approach for designing soft end-effectors for delicate, cluttered handling tasks in robotics.

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 method, we design a soft robot for reef rehabilitation, which grows and manipulates coral in onshore aquaculture facilities for future reef out-planting. We demonstrate ReefFlex increases both grasp success and grasp quality (disturbance resistance, positioning accuracy) and reduces in adverse events encountered during coral manipulation compared to reference designs. ReefFlex, offers a generalisable method to design soft end-effectors for complex handling and paves a pathway towards automation in previously unachievable domains like coral handling for restoration.
Paper Structure (15 sections, 1 equation, 7 figures)

This paper contains 15 sections, 1 equation, 7 figures.

Figures (7)

  • Figure 1: Live Coral grasped using ReefFlex at CHARM facility
  • Figure 2: Finger Design Domain
  • Figure 3: a) Complete numerical results of Passive Finger Optimisations illustrating Pareto front of the designs and trade-off between increasing displacement and reducing strain. b) Complete numerical results of active Finger Optimisations. c) Visualisation of representative selection of fingers under all six load cases (Left to Right: $F_{in1}$ to $F_{in6}$), where red is solid material and blue is void. d) Visualisation of selected fingers under four load cases (Left to Right: $F_{in1}$, $F_{in2}$, $F_{in3}$, $X_{in}$).
  • Figure 4: a) Simulated deformation profiles for selected optimised grippers when grasping fixed coral substrate. b-e) Grasp Performance Validation using Non-linear contact model with substrate. b) Contact force between gripper and substrate at full extension, c) Gripper Tip Stiffness, d) Shape adaptivity, the relative change in displacement between the gripper middle and tip when a force is applied at the middle of its contact face ($F_{in3}$), e) Maximum stress experienced by the gripper during substrate grasping. f) Illustration of shape adaptability of different grippers when grasping a simplified brain coral. Gripper $P(i)$ is able to adapt and conform to the coral geometry far better than $P(ii)$, the benchmark Fin Ray, or other optimised designs
  • Figure 5: (a) CHARM Robot and Raceway system, (b) ReefFlex Gripper assembly, showing major design components. Left: In open position, Right: closed position. c) Cam profile and corresponding barrel positions. d) Coral propagation tray with empty and coral containing plugs
  • ...and 2 more figures