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Insects navigate cluttered environments using slender, flexible antennae densely packed with mechanosensors, a lightweight, energy-efficient solution for tactile perception. We introduce CITRAS (Cockroach-Inspired Tactile Robotic Antenna Sensor), a miniature, compliant, multi-segment tactile probe aimed at enabling similarly capable close-range perception on insect-scale robots under stringent size, mass, and power constraints. CITRAS (total size: $\mathrm{\hspace{0.17em}}73.7\mathrm{\hspace{0.17em}}\times \mathrm{\hspace{0.17em}}15.6\mathrm{\hspace{0.17em}}\mathrm{mm}\mathrm{\hspace{0.17em}}\times \mathrm{\hspace{0.17em}}2.11\mathrm{\hspace{0.17em}}$mm; mass: $\mathrm{}491\mathrm{\hspace{0.17em}}\mathrm{mg}$) features eight flexural hinge segments, each with high-resolution capacitive sensors embedded within a compliant multilayer laminate structure, that detect femtofarad-scale capacitance changes induced by hinge deflection. Through systematic mechanical and sensing characterization under both quasi-static and dynamic conditions, we demonstrate sub-degree angular precision (max error $\mathrm{\le \hspace{0.17em}}\mathrm{}0.8$∘), accurate shape reconstruction, and consistent repeatable performance with minimal hysteresis in slow bending. Under rapid interactions, CITRAS exhibits low damping and rich dynamic responses that encode environmental features. We further validate the system in three core tactile tasks: estimating body-to-wall distance (error $\mathrm{\le \hspace{0.17em}}\mathrm{}8\mathrm{\%}$), measuring object gap width (error $\mathrm{\le \hspace{0.17em}}\mathrm{}7\mathrm{\%}$), and discriminating between smooth and rough surface textures via spatiotemporal tactile images. These results show that CITRAS delivers a compact, distributed, bioinspired tactile modality capable of reliable environment sensing, filling a critical gap in perception for insect-scale robots. Furthermore, the antenna consumes only $\mathrm{}32\mathrm{\hspace{0.17em}}\mathrm{mW}$(excluding MCU), making it suitable for future full deployment onboard insect-scale robots and thus paves the way for autonomous navigation and interaction in confined, unstructured, or delicate environments at this scale. 

Most biosensing techniques require complex processing steps that generate prolonged workflows and introduce potential points of error. Here, we report an acoustic pipette to purify and label biomarkers in 70 minutes. A key aspect of this technology is the use of functional negative acoustic contrast particles (fNACPs), which display biorecognition motifs for the specific capture of biomarkers from whole blood. Because of their large size and compressibility, the fNACPs robustly trap along the pressure antinodes of a standing wave and separate from blood components in under 60 seconds with >99% efficiency. fNACPs are subsequently fluorescently labeled in the pipette and are analyzed by both a custom, portable fluorimeter and flow cytometer. We demonstrate the detection of anti-ovalbumin antibodies from blood at picomolar levels (35 to 60 pM) with integrated controls showing minimal nonspecific adsorption. Overall, this system offers a simple and versatile approach for the rapid, sensitive, and specific capture of biomolecules. 

Animals are much better at running than robots. The difference in performance arises in the important dimensions of agility, range, and robustness. To understand the underlying causes for this performance gap, we compare natural and artificial technologies in the five subsystems critical for running: power, frame, actuation, sensing, and control. With few exceptions, engineering technologies meet or exceed the performance of their biological counterparts. We conclude that biology’s advantage over engineering arises from better integration of subsystems, and we identify four fundamental obstacles that roboticists must overcome. Toward this goal, we highlight promising research directions that have outsized potential to help future running robots achieve animal-level performance. 

Synopsis While animals swim, crawl, walk, and fly with apparent ease, building robots capable of robust locomotion remains a significant challenge. In this review, we draw attention to mechanosensation—the sensing of mechanical forces generated within and outside the body—as a key sense that enables robust locomotion in animals. We discuss differences between mechanosensation in animals and current robots with respect to (1) the encoding properties and distribution of mechanosensors and (2) the integration and regulation of mechanosensory feedback. We argue that robotics would benefit greatly from a detailed understanding of these aspects in animals. To that end, we highlight promising experimental and engineering approaches to study mechanosensation, emphasizing the mutual benefits for biologists and engineers that emerge from moving forward together. 

Planning locomotion trajectories for legged microrobots is challenging. This is because of their complex morphology, high frequency passive dynamics, and discontinuous contact interactions with their environment. Consequently, such research is often driven by time-consuming experimental methods. As an alternative, we present a framework for systematically modeling, planning, and controlling legged microrobots. We develop a three- dimensional dynamic model of a 1.5 g quadrupedal microrobot with complexity (e.g., number of degrees of freedom) similar to larger-scale legged robots. We then adapt a recently developed variational contact-implicit trajectory optimization method to generate feasible whole-body locomotion plans for this microrobot, and demonstrate that these plans can be tracked with simple joint-space controllers. We plan and execute periodic gaits at multiple stride frequencies and on various surfaces. These gaits achieve high per-cycle velocities, including a maximum of 10.87 mm/cycle, which is 15% faster than previously measured for this microrobot. Furthermore, we plan and execute a vertical jump of 9.96 mm, which is 78% of the microrobot’s center-of- mass height. To the best of our knowledge, this is the first end-to-end demonstration of planning and tracking whole-body dynamic locomotion on a millimeter-scale legged microrobot.