Animals
execute intelligent and efficient interactions with their
surroundings through neural pathways, exhibiting learning, memory,
and cognition. Artificial autonomous devices that generate self-optimizing
feedback mimicking biological systems are essential in pursuing future
intelligent robots. Here, we report an artificial neural pathway (ANP)
based on a memristor synapse to emulate neuromorphic learning behaviors.
In our ANP, optical stimulations are detected and converted into electrical
signals through a flexible perovskite photoreceptor. The acquired
electrical signals are further processed in a zeolitic imidazolate
frameworks-8 (ZIF-8)-based memristor device. By controlling the growth
of the ZIF-8 nanoparticles, the conductance of the memristor can be
finely modulated with electrical stimulations to mimic the modulation
of synaptic plasticity. The device is employed in the ANP to implement
synaptic functions of learning and memory. Subsequently, the synaptic
feedbacks are used to direct a robotic arm to perform responding motions.
Upon repeatedly “reviewing” the optical stimulation,
the ANP is able to learn, memorize, and complete the specific motions.
This work provides a promising strategy toward the design of intelligent
autonomous devices and bioinspired robots through memristor-based
systems.