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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 spatial-temporal patterns via the application of external cues or when confined within flexible boundaries. Like their natural counterparts, these approaches typically require many units to initiate collective motion, so controlling the ensuing dynamics is challenging. Here, we demonstrate a simple mechanism that leverages nonlinear elasticity to tame near-diffusive motile particles in forming structures capable of directed motion and other emergent 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 structures with boundaries, e.g., walls and constrictions, and demonstrate how they can exhibit remarkable emergent behaviors such as maze navigation. These findings demonstrate that allowing and understanding changes in body morphology can enhance the capabilities of active matter systems and enable the design of robotic materials capable of space exploration, adaptation, and complex interactions with their surrounding environment. 

Abstract The transition from small genetic to genome-scale datasets for studying biodiversity has revealed that genetic exchange through introgressive hybridization is a widespread phenomenon in nature. Despite this, a lack of high-quality reference genomes for most non-model species limits our understanding of the impact of this process for many taxonomic groups. This restricts the range of insights that genomic tools can provide for conservation biologists, who often hope to employ genomic datasets to accurately identify historically isolated lineages to protect and to predict their evolutionary fate in the face of environmental change. Tiger whiptail lizards (Aspidoscelis tigris complex) are an abundant and important ecological component of ecosystems across the southwestern United States. In this study, we assembled and annotated a chromosome-level reference genome for A. t. stejnegeri from coastal California. We then used this reference genome to reconstruct patterns of speciation and admixture within the larger species complex, finding evidence that gene flow is widespread both geographically and across the genome.