4.8 Article

Insect-Inspired, Spike-Based, in-Sensor, and Night-Time Collision Detector Based on Atomically Thin and Light-Sensitive Memtransistors

Journal

ACS NANO
Volume -, Issue -, Pages -

Publisher

AMER CHEMICAL SOC
DOI: 10.1021/acsnano.2c07877

Keywords

collision detection; low power; bioinspired; two-dimensional materials; circuits

Funding

  1. Army Research Office (ARO) [W911NF1920338]
  2. National Science Foundation (NSF) through CAREER Award [ECCS-2042154]
  3. National Science Foundation (NSF) through the Pennsylvania State University 2D Crystal Consortium - Materials Innovation Platform
  4. National Science Foundation (NSF) through the Pennsylvania State University 2D Crystal Consortium - Materials Innovation Platform (2DCCMIP) under NSF [DMR-1539916]

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Researchers have developed a night collision detector by combining insect-inspired collision detection algorithms with advanced optoelectronic integrated circuits. This detector eliminates the need for image capture and processing, yet it can respond timely to collision scenarios in various real-life situations at night.
Detecting a potential collision at night is a challenging task owing to the lack of discernible features that can be extracted from the available visual stimuli. To alert the driver or, alternatively, the maneuvering system of an autonomous vehicle, current technologies utilize resource draining and expensive solutions such as light detection and ranging (LiDAR) or image sensors coupled with extensive software running sophisticated algorithms. In contrast, insects perform the same task of collision detection with frugal neural resources. Even though the general architecture of separate sensing and processing modules is the same in insects and in image-sensor-based collision detectors, task-specific obstacle avoidance algorithms allow insects to reap substantial benefits in terms of size and energy. Here, we show that insect-inspired collision detection algorithms, when implemented in conjunction with in-sensor processing and enabled by innovative optoelectronic integrated circuits based on atomically thin and photosensitive memtransistor technology, can greatly simplify collision detection at night. The proposed collision detector eliminates the need for image capture and image processing yet demonstrates timely escape responses for cars on collision courses under various real-life scenarios at night. The collision detector also has a small footprint of similar to 40 mu m2 and consumes only a few hundred picojoules of energy. We strongly believe that the proposed collision detectors can augment existing sensors necessary for ensuring autonomous vehicular safety.

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