Embodied Stability in a Minimally-Actuated Soft Robot for Autonomous Exploration

Abstract

Soft robots offer an opportunity to embed intelligence directly into morphology, potentially reducing the need for continuous feedback regulation. We present an autonomous, minimally actuated multi-stable soft robot for exploration in confined and cluttered environments. The robot is composed of a serial chain of multi-stable elastic elements whose energy landscape encodes discrete, passively stable configurations, enabling reversible shape transformation and shape retention without sustained actuation. A single mobile pneumatic actuator triggers transitions between these stable states, producing complex three-dimensional configurations with minimal hardware complexity. Autonomy is achieved through the integration of nonlinear hybrid modeling, visual pose estimation, and sampling-based motion planning within a ROS2 framework. Rather than regulating continuous deformation, computation in our system selects and sequences mechanically admissible state transitions, while structural multi-stability provides inherent stabilization and memory. Experimental results demonstrate closed-loop navigation in cluttered environments using this distributed balance between mechanics and control.