For at overvåge miljøet og navigere i den virkelige verden bør robotten være i stand til at optage billeder og miljømålinger under forskellige baggrundslysforhold. I de senere år har forskere og ingeniører verden over arbejdet på at udvikle flere og mere avancerede sensorer til at integrere i robotter, overvågningssystemer eller andre enheder, der kan fornemme deres omgivelser.
Ifølge Memes Consulting har forskere fra Hong Kong Polytechnic University, Peking University, Yonsei University og Fudan University for nylig udviklet en ny type bionisk synssensor, der bruger en mekanisme, der kunstigt simulerer nethindens funktion og kan bruges i en række forskellige data blev indsamlet. under lysforhold. Denne bioniske synssensor er baseret på fototransistorer lavet af molybdændisulfid.
Foto af det biomimetiske synssensorarray (venstre); skematisk struktur af synssensorenheden og optisk mikroskopbillede (højre)
"Our research team started work on optoelectronic memory five years ago," said Yang Chai, one of the researchers who developed the vision sensor. "This emerging device can output light-dependent and history-dependent signals, enabling image integration. , Weak signal accumulation, spectral analysis and other complex image processing functions, the multi-functional integration of sensing, data storage and data processing into one device."
I 2018 udgav Yang Chai og hans kolleger det første papir om optoelektronisk hukommelse, hvori de introducerede en resistiv switching-hukommelsesenhed, der kan udføre lysregistrering og logiske operationer. Et år senere introducerede holdet en ny type fotoresistiv random access memory med tre forskellige funktioner. Specifikt kan den nye enhed fornemme miljøet, gemme informationen i hukommelsen og udføre neuromorfe visuelle forbehandlingsoperationer.
"We studied the concepts of near-sensor and in-sensor computing paradigms in 2020 and published our views in the field." Yang Chai continued, "This new research on biomimetic vision sensors builds on our On top of all previous efforts."
The intensity of ambient natural light varies widely, with a total range of 280 dB. When the human retina senses external light signals, it adjusts the light sensitivity of its photoreceptors (i.e., rods and cones) according to the strength of the signal. This ultimately enables the human eye to gradually adapt to varying levels of lighting, allowing it to see clearly in both dark and bright environments, an ability known as "visual adaptation."
"For example, when you enter a dark cinema from a bright hall, you can hardly see anything at first, but after a while in the cinema, it becomes easier to see things," explains Yang Chai. "This phenomenon is called scotopic adaptation. Conversely, if you go from a dark movie theater to a sunny outdoors, you'll feel very dazzled at first, and it takes a while to get used to seeing what's going on around you. The process The opposite of dark adaptation is called photopic adaptation."
The main goal of Yang Chai and his colleagues' recent work is to build a vision sensor inspired by the structure and function of the human retina. To do this, they first started by studying the human retina and then tried to design perceptual strategies that would allow them to artificially simulate visual adaptations.
State-of--billedsensorer baseret på CMOS-teknologi har typisk et begrænset dynamisk område på 70 dB. Dette dynamiske område er dog meget smallere end lysområdet for naturlige scener (280 dB).
"To achieve visual perception over a wide range of light intensities, researchers have explored the use of controlled optical apertures, liquid lenses, adjustable exposure times, and denoising algorithms in post-processing," said Yang Chai. "However, these Methods often require complex hardware and software resources."
Dark and light adaptation of biomimetic vision sensor arrays. (a) Schematic of the dark adaptation test: recognition of low-light images using an 8 x 8 pixel array in a dark environment. (b) Schematic diagram of light adaptation test: recognition of high-illuminance images using an 8 x 8 pixel array in a bright environment. (c) Dark adaptation process to identify the "8" pattern. (d) The photoadaptation process to identify the "8" pattern.
Optoelektroniske enheder med let-adaptivt syn og bredt sanseområde ved sensoriske terminaler kan have meget værdifulde anvendelser. For eksempel kan de hjælpe med at forbedre ydeevnen af computervisionsværktøjer, reducere hardwarekompleksiteten, der kræves for at bygge robotter eller andre sensorsystemer, og forbedre nøjagtigheden af billedgenkendelsessystemer.
Selvom andre forskerhold tidligere har udviklet optoelektroniske enheder, der kan tilpasse sig forskellige lysforhold. De fleste af de tidligere demonstrerede enheder kan dog kun efterligne lystilpasningsmekanismen i nethinden. Den mørke tilpasningsproces har indtil videre vist sig sværere at simulere.
"There is still a long way to go to fully replicate the visual adaptation function of the retina," explains Yang Chai. "To achieve this, we designed a phototransistor-based vision sensor using ultra-thin semiconductors that can The degree of dark adaptation and light adaptation in the same device was controlled by applying different gate voltages. In this way, we simulated photoreceptors and horizontal cells in the retina and successfully achieved a sensing range of 199 dB. Vision-adaptive devices in biomimetic sensors."
Kunstig simulering af fotoreceptorer og horisontale celler i nethinden til visuel tilpasning (mørketilpasning og lystilpasning)
Den biomimetiske synssensor udviklet af Yang Chai og kolleger er baseret på fototransistorer lavet af et ultratyndt halvledermateriale kendt som molybdændisulfid. De fototransistorer, de brugte, har flere ladningsfældetilstande, der kan fange eller frigive elektroner i kanalen ved forskellige gatespændinger.
Ultimately, these states allow researchers to dynamically tune the conductance of their devices. This, in turn, allowed them to artificially simulate the dark- and light-adaptive mechanisms of the human retina, thereby expanding the range of their sensor's perception of different lighting conditions.
"Our bionic vision sensor has several advantages and features," said Yang Chai. "First, the visual adaptation function is implemented in a single device, which greatly reduces the footprint. Second, multiple functions can be implemented on a single device. , including light sensing, memory, and processing. Finally, dark and light adaptation under different light intensities can be achieved by controlling its gate voltage."
Yang Chai og hans kolleger evaluerede den bioniske synssensor i en række tests og fandt ud af, at den effektivt kunne efterligne funktionen af den menneskelige nethinde og opnå bemærkelsesværdige resultater i både mørke- og lystilpasning. Ydermere har den et betydeligt højere perceptuelt område (199 dB) sammenlignet med tidligere foreslåede løsninger.
"Our vision sensor can enrich machine vision functions, reduce hardware complexity, and achieve high image recognition efficiency," said Yang Chai, "All these advantages are available in areas such as autonomous driving, face recognition, and industrial manufacturing in complex lighting environments. great application prospects."
I fremtidige undersøgelser planlægger forskerne at forbedre ydeevnen af synssensoren yderligere, mens de også bruger den til at fremstille store-systemer bestående af sensorarrays. Ideelt set ønsker de at bygge dette sensorarray på et fleksibelt eller halvkugleformet substrat for at muliggøre et bredere synsfelt.
"One area that needs improvement is the adaptation time of our vision sensor, as it is still not enough to support machine vision applications." Yang Chai added, "Our goal is to reduce the adaptation time to the microsecond level. In addition, the vision sensor array scale Further improvements are also needed. Our near-term target for array size is greater than 100 x 100 pixels. Finally, the heterogeneous integration of vision sensors and post-processing units, including silicon-based control circuits, is a very important step toward practical applications."
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