Gaussian Process-Based Gait Optimization of a Cable-Driven Soft Quadruped Robot

Abstract

Soft robots offer significant advantages over rigid-bodied counterparts due to their inherent flexibility and deformability. However, these same characteristics often introduce challenges in control and simulation-to-reality (Sim-to-Real) synchronization. In this study, we quantified the locomotion performance of a soft quadruped robot through experimental trials. To alleviate the burden of exhaustive physical testing over an expanded parameter space, we employed a Gaussian process-based optimization framework.