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Abstract Bio-inspired robot controllers are becoming more complex as we strive to make them more robust to, and flexible in, noisy, real-world environments. A stable heteroclinic network (SHN) is a dynamical system that produces cyclical state transitions using noisy input. SHN-based robot controllers enable sensory input to be integrated at the phase-space level of the controller, thus simplifying sensor-integrated, robot control methods. In this work, we investigate the mechanism that drives branching state trajectories in SHNs. We liken the branching state trajectories to decision-splits imposed into the system, which opens the door for more sophisticated controls -- all driven by sensory input. This work provides guidelines to systematically define an SHN topology, and increase the rate at which desired decision states in the topology are chosen. Ultimately, we are able to control the rate at which desired decision states activate for input signal-to-noise ratios across six orders of magnitude. 

Shape‐morphing capabilities of metamaterials can be expanded by developing approaches that enable the integration of different types of cellular structures. Herein, a rational material design process is presented that fits together auxetic (anti‐tetrachiral) and non‐auxetic (the novel nodal honeycomb) lattice structures with a shared grid of nodes to obtain desired values of Poisson's ratios and Young's moduli. Through this scheme, deformation properties can be easily set piece by piece and 3D printed in useful combinations. For example, such nodally integrated tubular lattice structures undergo worm‐like peristalsis or snake‐like undulations that result in faster speeds than the monophasic counterpart in narrow channels and in wider channels, respectively. In a certain scenario, the worm‐like hybrid metamaterial structure traverses between confined spaces that are otherwise impassable for the isotropic variant. These deformation mechanisms allow us to design shape‐morphing structures into customizable soft robot skins that have improved performance in confined spaces. The presented analytical material design approach can make metamaterials more accessible for applications not only in soft robotics but also in medical devices or consumer products.