  Active systems of self-propelled agents, e.g., birds, fish, and bacteria, can
organize their collective motion into myriad autonomous behaviors. Ubiquitous
in nature and across length scales, such phenomena are also amenable to
artificial settings, e.g., where brainless self-propelled robots orchestrate
their movements into spatio-temportal patterns via the application of external
cues or when confined within flexible boundaries. Very much like their natural
counterparts, these approaches typically require many units to initiate
collective motion such that controlling the ensuing dynamics is challenging.
Here, we demonstrate a novel yet simple mechanism that leverages nonlinear
elasticity to tame near-diffusive motile particles in forming structures
capable of directed motion and other emergent intelligent behaviors. Our
elasto-active system comprises two centimeter-sized self-propelled microbots
connected with elastic beams. These microbots exert forces that suffice to
buckle the beam and set the structure in motion. We first rationalize the
physics of the interaction between the beam and the microbots. Then we use
reduced order models to predict the interactions of our elasto-active structure
with boundaries, e.g., walls and constrictions, and demonstrate how they can
exhibit intelligent behaviors such as maze navigation. The findings are
relevant to designing intelligent materials or soft robots capable of
autonomous space exploration, adaptation, and interaction with the surrounding
environment.
