SoftSling: A Soft Robotic Arm Control Strategy to Throw Objects With Circular Run-Ups

In this letter, we present SoftSling, a soft robot control strategy designed for accurately throwing objects following circular run-ups. SoftSling draws inspiration from ancient slingers, who rotated a sling loaded with a projectile at high speeds to fight and hunt, releasing the object by letting go of the sling's end. Our study aims to replicate this behavior by exploiting the embodied intelligence of soft robots under periodic actuation input, that enables them to generate self-stabilizing motions. The periodic input parameters for moving along a circular-like path are generated by a neural network based on the weight of the object and the target position. Subsequently, a separate neural network model predicts the release time by considering the gripper opening delay and the object positions during motion. We tested this strategy on a modular soft robot, I-Support, by throwing three objects of varying weights into 140-mm square target boxes. We achieved a success rate ranging from 75% to 88% for different objects, with the heaviest object yielding the highest success rate. Our research contributes to integrating soft robots into everyday life, enabling them to perform complex and dynamic tasks.