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Daga cikin ƙarfin robotika a yau, AMR (robotin mobile mai gaskiya) ya zama tsarin yadda ake ƙara kuma a cikin tattalin arziki, sayarwa, aljumaa da sauran al’adu. Wadannan roboti suna iya tattara daga baya, kari mabudai da aiki, wanda ya kara yawa kuma fahimta da karamin aiki. Wadannan kamerun da suka shiga cikinsu ne suka ba su hankali na yadda suka yi aiki. Kameru ita ce "kunyi" na roboti, kuma amsar da shi da karamin su ya kara yawa kuma karamin aikinsu da karamin amfani da su.
A matsayin malamin da ke nufin kamerun, wannan rubutu zai bayyana tausayi kamar yadda ake amfani da wadannan biyu nawa na kamerun da suka amfani da su a cikin AMR: 2D vision da 3D vision. Mu zai bayyana kamar yadda ake amfani da kamerun a cikin AMR, kamar yadda ake amfani da shutter, yadda ake amfani da interface, da teknologiya na 3D vision, mu bai ingantaccen bayani ga masu amfani da kamerun a cikin roboti.
Biyan nawa na kamerun da suka amfani da su a cikin AMR
A cikin ma'ajin AMR, kamerun da aka fitar da su ne biyu: kamerun da suka nemo 2D da kamerun da suka nemo 3D. Wato kamar yadda suka amfani da su a fahimta na al'umma, suna da wani farko na aiki da lokacin da suka amfani da su.
1. Kamerun da suka nemo 2D don AMR
Wadannan kamerun suna kamar wadanda muna ganin su kafin kowace rana, kuma suna gano bayanan taswira ta 2D. Suna ne daga cikin kamar kamarin da suka nemo da suka nemo na AMR.
Wadanda aikin da kamerun da suka nemo 2D suna iya amfani da su suna: SLAM na taswira (don tattara da kariya na sarrafa da kariya), nemo koda na QR ko koda na barcode, da nemo da kariya na abubuwa masu siffi da kariya. Suna da karami mai yawa da karami mai yawa da amfani da su, kuma suna ne daga cikin kamar kamarin da suka nemo na AMR.
2. Kamerun da suka nemo 3D don AMR
Wadannan kamerun suna nemo taswirai kuma suna nemo bayanan gaba (depth) na al'umma don samun model na 3D. Wannan yana ba da amfani ga robotin don fahimta girma, tsawo da yankin abubuwa.
Kamar yadda ake amfani da kamerun 3D don ganin ƙarfi, suka haɗa ne: karewa da abubuwa masu daga cikin bayanai mai tsoro, saba wa kusura ko kusurun da aka saita daidai, da kuma aiki na kuskurwa don robotun da suka kuskurwa abubuwa. Ganin 3D ya ba roboti bayanai mai yawa daga cikin al'ada, wanda ke taimaka su a gudumta abubuwan da suka fiye da maki.
Matsayin Muhimmanci Don Gano Wajen Zuba Kamerun 2D
Wanindan da suka zuba kamerun 2D don AMR, masu inganta suna bukata yadda ake nufin da matsayin muhimmanci. Wannan ba ta fahimci kuma kwalitinkan taswira, amma ta fahimci kuma taimakawa da karamin roboti da kuma karamin yin aiki.
1. Ido na Shutter: Rolling Shutter vs. Global Shutter Robot Vision
Idon shutter ita ce babban wani abu don ganin roboti. Rolling shutter ya tashi taswira ta kalmomi, wanda ke nuna "jello effect" ko taswirar da aka bincika lokacin da roboti ya tafi da yawa. Wannan shine abu muhimmanci don AMR, wadanda suka bukata yadda ake tafiya daidai da kuma ganin abubuwa.
Wata ƙarshen, shaterin global yana kira dukkan tashin taswira a lokaci daya, ta hanyar yin taswirorin da ba su da ƙarfi ba, wanda ke nufin cewa suna da alama na tsoro ba, kuma a lokacin da aka sauya taswirorin da suka gudan, ko a lokacin da aka sauya taswirorin da suka gudan. Don AMRs da suka buƙatar fahimtar abubuwan da suka gudan ko aikata a wurare da suka gudan, shaterin global shine zane mai kyau, amma yana da karamin kariya.
2. Tsawon Sensor da Karamin Tashin Taswira
Tsawon mai kyau yana ba da fahimtar mai kyau, wanda ke manta don fahimtar QR code, karatu littafi, ko fahimtar abubuwan da suka gudan. Amma, tsawon mai kyau yana da karamin kariya da yin karamin karamin tashin taswira da karamin karamin processor. Masu inganta suna buƙatar yin karamin tsawon da karamin tashin taswira don tabbatar da robot ya iya aiki da data na taswira a lokacin da suka gudan da yin aiki da karamin kariya.
3. Tsawon Lens da Tsoro
Filin gani (FOV) na kyamarar hangen nesa ta 2D yana ƙayyade kewayon yanayin robot. Babban FOV yana da mahimmanci don kewayawa da taswirar robot. Koyaya, ruwan tabarau mai faɗi sau da yawa yana gabatar da ɓatar da hoto, wanda ke buƙatar gyara ta hanyar algorithms na software; in ba haka ba, ƙimar kewayawa na iya shafar.
4. Ka yi tunani a kan wannan. Zaɓuɓɓukan Interface: Zaɓuɓɓukan Interface na Kamara (USB, MIPI CSI, GMSL2, GigE) don AMRs
Zaɓin ƙirar kyamara yana tasiri kai tsaye saurin canja wurin bayanai, tsawon kebul, da rikitarwa na tsarin.
MIPI CSI yana ba da babban bandwidth da ƙananan amfani da wutar lantarki, yana mai da shi manufa don kyamarori masu sauƙi don AMRs. Amma, tsawon igiyar yana da iyaka.
Ƙungiyar USB tana da sauƙi kuma mai sauƙi don amfani, amma yana iya cinye albarkatun mai sarrafawa kuma yana da iyakancewar bandwidth lokacin da ake amfani da kyamarori da yawa a lokaci guda.
Kwayar GigE (Gigabit Ethernet) ta sanya damuwa da yawa da kuma tana da tsoro mai ƙarfi, amma ta ci gaba da kwana mai yawa da kuma zai iya bukata kardin netwak na farko.
Kwayar GMSL2 (Gigabit Multimedia Serial Link) shi ne kwayar al'ummar masu gudunmawa wanda ya sanya damuwa da yawa da kuma damuwa na madaidaici na kamerun, kuma shi ne zaɓi mai kyau don sistemun AMR mai yawa. Amma yana da abin fuskansa mai yawa.
Muhimmancin bayanin da ke cikin saƙo na kamarin kamerun na 3D
A duk wadanda suka bayani a sama a baya don kamerun na 2D, lokacin da aka zaɓi kamerun na 3D don AMR, yana muhimmi a gano akan wannan muhimmancin bayanin teknik.
1. Idojin 3D: Kamarin biyu, Lokacin da aka fiye, da Kamarin da aka raba
Stereo vision yana amfani da biyu kamerun don samun bayani na gaba ta hanyar yin hisabai na farko, wanda ke nufin yin bayani na gaba. Bayanin da aka fuskanci shine ya kamata yin amfani da abubuwan da suka dace da yadda yake aiki kuma yana bukatar ƙananin alama. Bayanin da aka fuskanci shine yana aiki ta hanyar tsohon kuma ba ta gane ba da sautin yadda yake aiki, wanda ke nufin yin amfani da shi a waje.
Time of Flight (ToF) yana hisabinsa na yadda yake aiki ta hanyar yin hisabinsa na lokacin da ke cikin rabi na tsawon zafi. Bayanin da aka fuskanci shine yana da kyau a yadda yake aiki da yadda yake aiki kuma yana da ƙananin alama na hisabinsa. Bayanin da aka fuskanci shine yana da ƙananin alama na yadda yake aiki kuma yana da kuzari a lokacin da ke cikin rabi na tsawon zafi.
Structured light yana nuna abubuwa na yadda yake aiki ta hanyar nuna abubuwa na yadda yake aiki a cikin wani wurin da ke cikin wani tsari kuma yana yin hisabinsa na yadda yake aiki ta hanyar yin hisabinsa na farko na tsari. Bayanin da aka fuskanci shine yana da kyau a yadda yake aiki. Bayanin da aka fuskanci shine yana da kuzari a lokacin da ke cikin rabi na tsawon zafi kuma yana da kuzari a yadda yake aiki.
2. Kyau na yadda yake aiki kuma yadda yake aiki
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3. Ka yi tunani a kan wannan. Bukatar Mai sarrafawa da Amfani da Wutar Lantarki
ganin 3D yawanci yana buƙatar sarrafa bayanai da yawa fiye da hangen nesa na 2D. Dukansu lissafin bambancin bincular da kuma sarrafa bayanan girgije suna buƙatar mai sarrafawa mai ƙarfi. Wannan yana gabatar da mahimmin ciwo ga AMRs masu amfani da batir. Injiniyoyi suna buƙatar la'akari da ko tsarin kyamarar yana da mai sarrafa 3D da aka gina kuma ko kayan aikin haɓaka software (SDK) yana da inganci don tabbatar da rayuwar batirin robot da aikinsa.
Bayan fikir
Za a iya zama ƙarfi da kariya wani amfanin teknikal don zaɓar kamera mai gudunmawa don AMR, wanda ya bukatar fahimtar cikakken yadda 2D da 3D suna ci gaba da kariya su da kariyar su. Daga zaɓar bayan shutter mai rarraba da shutter mai gaba kuma yadda ake tashin kamarai na kamera, kowanne daga waɗannan yadda ake yi shi yana da mahimmanci. Zaɓar kamarai mai gudunmawa yana da mahimmanci don aiki mai kyau na robot da yadda ake samun kariya na project.
Muchvision ta taimaka da zaɓar AMR
Ku ƙara kariya a zaɓar kamarai mai gudunmawa don project-in kuka? Samu wasu masu ilmi na mu a yau kuma mu za mu ba ku da kamarai na musamman da ayyukan taimakawa na gudunmawa don taimakawa ku a bincike AMR mai kyau!
