Neuromorphic touch for robotics—a review

摘要

Abstract The field of neuromorphic tactile sensing aims to emulate the biological mechanisms of touch to enable artificial systems with efficiency, adaptability, and precision akin to natural tactile perception. Inspired by the spike-based data encoding of biological mechanoreceptors and neural processing, neuromorphic tactile sensors (NTSs) leverage event-driven architectures to handle sensory information through sparse, low-power, and efficient formats. This review explores the state of neuromorphic tactile sensing, emphasizing its biological foundations, sensor technologies and encoding techniques within the field of robotics. By bridging biological touch mechanisms with neuromorphic engineering, NTSs have the potential to enhance robotic manipulation, prosthetics, and human–machine interfaces. Challenges and future directions include developing novel materials for sensors, improving the performance of spiking neural networks and lowering the barrier to entry into neuromorphic touch research through open-sourcing code and datasets. This review underscores the potential of neuromorphic tactile sensing in creating highly efficient and versatile tactile systems for robotics and beyond.