Light Intensity‐Driven Bidirectional Photoresponse Vision Sensor for Autonomous Obstacle Avoidance System

Abstract

ABSTRACT Bio‐inspired vision sensors emulating neural‐pathway processing hold significant promise for next‐generation robotics and artificial intelligence. However, achieving biomimetic threat‐distance adaptation, where escape initiation dynamically calibrates to looming object proximity within a single device as in insect neural circuits, remains challenging for bionic vision systems implementations. Herein, we present a vision sensor based on a 2D PVK/h‐BN/MoS 2 /h‐BN/2D PVK heterostructure that achieves full dynamic emulation of insect phototactic/scototactic behaviors. The core innovation is symmetrical gate‐field co‐regulation, opposing gate biases on the top and bottom 2D PVK photosensitive layers trigger antagonistic field‐effect modulation in response to light gradients. Low light intensity activates the top layer, inducing persistent positive photocurrent (PPC) via hole/cation accumulation, while high light intensity activates the bottom layer, generating negative photoconductivity (NPC) via electron/anion accumulation, mimicking adjacent ommatidial excitation/inhibition. Hopping‐like ion transport enables ultra‐long PPC/NPC persistence post‐illumination. An autonomous obstacle avoidance system built with this sensor directly maps light‐gradient signals to motor commands enabling voltage‐tunable braking distance control via symmetric gate differential modulation, co‐processing real‐time intensity, historical accumulation, and rate‐of‐change for efficient collision avoidance in dynamic environments. This work provides a valuable reference scheme for bionic vision systems.