Physically intelligent soft antennae enhance tactile perception by active touch

Soft robotic sensors today struggle to interpret complex tactile scenes without incurring significant computational costs. Inspired by insect antennae—soft, distributed sensors that efficiently process tactile information through physical intelligence—we investigated whether mechanical design and active touch sensing strategies could enhance robotic tactile feature perception. We hypothesized that insect-inspired antenna dynamics, specifically stiffness gradients and active touch speed, could simplify tactile classification. Using bioinspired computational and robophysical models of cockroach antennae, we introduce the notion of tactile tensors—spatiotemporal representations of tactile stimuli shaped by contact location, feature type, and active touch speed. Our analyses show that cockroach-inspired antenna mechanics and active touch speeds significantly improve feature classification accuracy compared to conventional sensors by increasing tactile data sparsity and dispersion. Through sim-to-real transfer, these principles were successfully demonstrated on a miniature distributed soft robotic antenna, validating their effectiveness in real-world robotic systems. Unlike robotic vision systems—which also use distributed sensing but cannot leverage mechanical gradients and contact dynamics—our approach achieves efficient sensing through physically intelligent, adaptive mechanics. Our work for the first time demonstrates how active movement of a mechanically tuned soft, distributed tactile sensor enhances robotic perception. Taken together, this work presents a biologically grounded framework for tactile sensor design that reduces computational load and enhances adaptability.