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The widespread implementation and rapid development of autonomous systems pose stringent performance requirements on emerging sensory systems. In addition to the basic sensing requirements, leading sensory systems are required to process data and extract featured information from highly redundant data in real time. With the added edge‐computational capabilities, data shuttling is avoided, leading to significant reduction of computational burden and bandwidth pressure in the cloud. Among the different computing architectures, the neuromorphic sensory system stands out due to its high power efficiency, low latency, and excellent processing capability. Mimicking the biological neural network, the colocation of sensory, processor, and memory components of neuromorphic sensory systems enables the requirements for frequent data shuttles to be circumvented. In particular, artificial intelligent perceptions built on memristive neuromorphic systems exhibit outstanding characteristics of small footprint, low power consumption, 3D stacking ability, and high density. Herein, the two essential parts of the memristive artificial perceptron system are presented: 1) memristive systems for neuromorphic computing and 2) high‐performance sensors. Next, the current state of the art established on artificial perceptron systems covering visual, auditory, and tactile sensations is highlighted. To conclude, the current challenges and future direction in the area of advanced intelligent perceptions are presented.
Ji et al. (Fri,) studied this question.