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A low-power biomimetic collision detector based on an in-memory molybdenum disulfide photodetector


Accurately detecting a potential collision and triggering a timely escape response is critical in the field of robotics and autonomous vehicle safety. The lobula giant movement detector (LGMD) neuron in locusts can detect an approaching object and prevent collisions within a swarm of millions of locusts. This single neuronal cell performs nonlinear mathematical operations on visual stimuli to elicit an escape response with minimal energy expenditure. Collision avoidance models based on image processing algorithms have been implemented using analogue very-large-scale-integration designs, but none is as efficient as this neuron in terms of energy consumption or size. Here we report a nanoscale collision detector that mimics the escape response of the LGMD neuron. The detector comprises a monolayer molybdenum disulfide photodetector stacked on top of a non-volatile and programmable floating-gate memory architecture. It consumes a small amount of energy (in the range of nanojoules) and has a small device footprint (~1 µm × 5 µm).

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Fig. 1: Biological and artificial collision detectors.
Fig. 2: Monolayer MoS2 photodetector and its response to looming stimuli.
Fig. 3: Inhibitory response of MoS2 FET to programming stimuli.
Fig. 4: Mimicking the escape response of LGMD neurons.
Fig. 5: Compact model for a biomimetic collision detector.

Data availability

The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.

Code availability

The codes used for plotting the data are available from the corresponding author on reasonable request.


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This work was partially supported through grant number FA9550-17-1-0018 from the Air Force Office of Scientific Research (AFOSR) through the Young Investigator Program and Army Research Office (ARO) through contract no. W911NF1920338. We also acknowledge the support from the National Science Foundation (NSF) through the Pennsylvania State University’s 2D Crystal Consortium–Materials Innovation Platform (2DCC-MIP) under NSF cooperative agreement DMR-1539916.

Author information




S.D. conceived the idea, designed the experiments and wrote the manuscript. D.J., A.O. and S.D. performed the experiments, analysed the data, discussed the results and agreed on their implications. A.S. fabricated the devices. T.H.C. synthesized the MoS2 monolayers. All the authors contributed to the preparation of the manuscript.

Corresponding author

Correspondence to Saptarshi Das.

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The authors declare no competing interests.

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Supplementary information

Supplementary Information

Supplementary Table 1, Figs. 1–18 and discussions 1–15.

Supplementary Video 1

Scenario depicting a car approaching the collision detector on a direct collision course.

Supplementary Video 2

Visual excitation experienced by the collision detector from an approaching car.

Supplementary Video 3

Scenario depicting a car approaching a wall and the corresponding visual excitation experienced by the collision detector from the reflected light.

Supplementary Video 4

Visual excitation due to increasing light intensity from a static source.

Supplementary Video 5

Simulated escape response from a multipixel collision detector array.

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Jayachandran, D., Oberoi, A., Sebastian, A. et al. A low-power biomimetic collision detector based on an in-memory molybdenum disulfide photodetector. Nat Electron 3, 646–655 (2020).

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