Overview
Visual SLAM inoita kuti kamera inofamba ivake mepu yenzvimbo isingazivikanwe panguva imwe chete ichitevera chinzvimbo chayo mukati mepu iyoyo. Ndiyo nzvimbo yekumusana yemarobhoti, drones, AR mahedhifoni, uye kuzvityaira zvinhu.
Visual SLAM ndeyekombuta-yekuona workflows inodudzira kana kugadzira midhiya yekuona yekuongorora, mashandiro, uye kugadzira.
Deep Dive
SLAM inomiririra Panguva imwe chete Yekugarisana uye Mepu, uye iyo yekuona musiyano inoigadzirisa uchishandisa makamera pane (kana padivi) lidar kana radar. Sezvo kamera inofamba, iyo sisitimu inoona akasiyana maficha senge makona uye mipendero, inoafananidza nepakati pemafuremu, uye inoshandisa inooneka mafambiro emapoinzi iwayo kufungidzira ese ari maviri 3D chimiro chechiitiko uye trajectory yekamera. Chikamu chakaoma ndechekubatana kwehuku-nezai: unoda mepu kuti uzive pauri, asi unofanirwa kuziva kwauri kuti uvake mepu. Visual SLAM inobata izvi zvakabatana, kazhinji ichinatsa zviuru zvemapoinzi uye inomira kamwechete. Inopa simba ARKit, ARCore, Meta Kutsvaga mukati-kunze kwekutevera, maMars rovers, uye marobhoti anochengeterwa zvinhu, achishanda mumba umo GPS inotadza.
Technical Insight
Iyo pombi yakajairwa ine kumberi kumagumo inoteedzera furemu kuforemu (uchishandisa ORB, SIFT, kana nzira dzakanangana dzemafotometric) uye nekumashure kunokwirisa mepu. Kugadziriswa kwebundle pamwe chete kunoderedza kukanganisa kukanganisa pamakamera akawanda uye mapoinzi e3D, uku kuvharwa kwe loop kunoona kana kamera ikashanyirazve imwe nzvimbo uye kugadzirisa yakaunganidzwa. Monocular SLAM haigone kudzoreredza chikero chakakwana, saka makamera estereo kana inertial yekuyera unit (IMU) anosanganiswa kuti agadzirise.
Kubata Visual SLAM
Visual SLAM inoita kuti kamera inofamba ivake mepu yenzvimbo isingazivikanwe panguva imwe chete ichitevera chinzvimbo chayo mukati mepu iyoyo. Ndiyo nzvimbo yekumusana yemarobhoti, drones, AR mahedhifoni, uye kuzvityaira zvinhu. Visual SLAM ndeyekombuta-yekuona workflows inodudzira kana kugadzira midhiya yekuona yekuongorora, mashandiro, uye kugadzira. Kuvaka kunzwisisa kwakadzama, bata Visual SLAM semuenzaniso wekushandisa, kwete chinhu chimwe chete: tsanangura zvinodikanwa, kujekesa fungidziro, uye patsanura izvo zvinogona kuitwa nehurongwa hwakavimbika kubva kune zvichiri kuda kutonga kwenyanzvi.
Mukuita, zvikwata zvakasimba zvinoshandisa Visual SLAM chiyero chechokwadi nezvinhu zvekushanda semhando yedata, kusiyana kwemwenje, uye kuenderana kwemazita. Ivo vanonyora zvakajeka maitiro ebudiriro, bvunzo vachipokana ne data rechokwadi uye mafambiro ebasa, uye iterate zvichibva pane zvakacherechedzwa maitiro ekutadza kwete kuhwina-nguva imwe chete yebhenji. Apa ndipo apo kunzwisisa kwe theoretical kunoshanduka kuve kugona kwakasimba pane chigadzirwa, mutemo, uye mashandiro.
Visual AI inogona kuita otomatiki yekuongorora, yekuona, uye yekumaka mabasa pachiyero. Panguva imwecheteyo, kodzero dzeMufananidzo uye kubvumirwa kunogona kuve njodzi dzepamutemo kana hunhu husina kujeka. Nzira yakatsiga ndeyekubatanidza kukurumidza kuyedza nekutonga: mhanyisa vatyairi vendege, tora humbowo, buritsa matanda esarudzo, uye urambe uchivandudza chengetedzo semaitiro emuenzaniso, zvinotarisirwa nemushandisi, uye zvinodikanwa zvekutonga.
Strategic Impact
Visual AI inogona kuita otomatiki yekuongorora, yekuona, uye yekumaka mabasa pachiyero.
Visual AI inogona kuita otomatiki yekuongorora, yekuona, uye yekumaka mabasa pachiyero. Mukutumirwa kwemhando yepamusoro, izvi zvinoshandurirwa kuita mitemo inoyerwa yekushanda, miganhu yevaridzi, uye tsika dzekudzokorora dzinodzokororwa kuitira kuti zvikwata zvikwire kuvimba pane kukwidza kusajeka.
Zvikwata zvekugadzira zvinogona prototype pfungwa nekukurumidza nekudzokororwa kwemaoko mashoma.
Zvikwata zvekugadzira zvinogona prototype pfungwa nekukurumidza nekudzokororwa kwemaoko mashoma. Mukutumirwa kwemhando yepamusoro, izvi zvinoshandurirwa kuita mitemo inoyerwa yekushanda, miganhu yevaridzi, uye tsika dzekudzokorora dzinodzokororwa kuitira kuti zvikwata zvikwire kuvimba pane kukwidza kusajeka.
Mashandisirwo anogona kushandisa masaini emifananidzo nemavhidhiyo ayo aimbove akaoma kugadzirisa.
Mashandisirwo anogona kushandisa masaini emifananidzo nemavhidhiyo ayo aimbove akaoma kugadzirisa. Mukutumirwa kwemhando yepamusoro, izvi zvinoshandurirwa kuita mitemo inoyerwa yekushanda, miganhu yevaridzi, uye tsika dzekudzokorora dzinodzokororwa kuitira kuti zvikwata zvikwire kuvimba pane kukwidza kusajeka.
Real-World Implementation
Yemukati-kunze yekutevera yekutevera pa Meta Kuda uye Apple Vision Pro mahedhifoni, kutsvaga mushandisi mukamuri isina zviteshi zvekunze.
Apple ARKit uye Google ARCore inotsigira fenicha chaiyo kana mavara emutambo kune uriri chaihwo nematafura pamafoni.
NASA's Mars rovers inoshandisa inoona odometry uye mepu kufamba munzvimbo isina GPS.
Autonomous warehouse marobhoti uye indoor kutakura marobhoti anovaka uriri mepu uye nekugara pakati pemasherufu
Maitiro Ekuita
Visual SLAM mukuita
Mukati-kunze kwenzvimbo yekutevera pa Meta Kutsvaga uye Apple Vision Pro mahedhifoni, kutsvaga mushandisi mukamuri isina zviteshi zvekunze.
Mukati-kunze kwenzvimbo yekutevera pa Meta Kutsvaga uye Apple Vision Pro mahedhifoni, kutsvaga mushandisi mukamuri isina ekunze zviteshi zvezviteshi Matimu anowanzo kuwana mibairo iri nani kana achinge atsanangura emhando yepamusoro kumberi, chengetedza nzira yekukwira kwevanhu yemakesi emupendero, uye kuteedzera zvese zvakawanikwa zvechigadzirwa uye mutengo wekukanganisa nekufamba kwenguva.
Visual SLAM mukuita
Apple ARKit uye Google ARCore inotsigira fenicha chaiyo kana mavara emutambo pauriri chaihwo nematafura pamafoni.
Apple ARKit uye Google ARCore inotsigira fenicha chaiyo kana mavara emitambo kumafurati chaiwo nematafura pamafoni Zvikwata zvinowanzowana mibairo iri nani kana vachinge vatsanangura zvikumbaridzo zvemhando yepamusoro kumberi, chengetedza nzira yekukwira kwevanhu yemakesi emupendero, uye kuteedzera zvese zvakawanikwa zvechigadzirwa nemitengo yekukanganisa nekufamba kwenguva.
Visual SLAM mukuita
NASA's Mars rovers inoshandisa inoona odometry uye mepu kufamba munzvimbo isina GPS.
NASA's Mars rovers inoshandisa inoona odometry uye mepu yekufamba munzvimbo isina GPS Matimu anowanzo kuwana zvirinani zvibodzwa kana achinge atsanangura emhando yepamusoro kumberi, chengetedza nzira yekukwira kwevanhu yemakesi emupendero, uye kuteedzera zvese zvakawanikwa zvechigadzirwa nemitengo yekukanganisa nekufamba kwenguva.
Visual SLAM mukuita
Autonomous warehouse marobhoti uye emukati ekutakura marobhoti anovaka uriri mepu uye nekugara pakati pemasherufu.
Autonomous warehouse marobhoti uye emukati ekutakura marobhoti anovaka uriri mepu uye kugara pakati pemasherufu Matimu anowanzo kuwana mhedzisiro iri nani kana achinge atsanangura emhando yepamusoro kumberi, chengetedza nzira yekukwira kwevanhu yemakesi ekumucheto, uye kuteedzera zvese zvakawanikwa zvechigadzirwa nemitengo yekukanganisa nekufamba kwenguva.
Njodzi & Guardrails
Kodzero dzemifananidzo uye kubvumirwa kunogona kuve njodzi dzepamutemo kana provenance isina kujeka.
Kuita kwemuenzaniso kunogona kusiyanisa kupenya, huwandu hwevanhu, uye nharaunda.
Manyepo enhema anogona kusacherechedzwa kunze kwekunge zvikumbaridzo zvekuvimba zvikatariswa.
Implementation Roadmap
Tsanangura maitiro ekugamuchirwa echokwadi, kurangarira, uye mutengo wekukanganisa.
Tsanangura maitiro ekugamuchirwa echokwadi, kurangarira, uye mutengo wekukanganisa. Bata nhanho yega yega segedhi rehumbowo: kana maitiro asina kusangana, imbomira kuburitsa, vhara gaka, uye wobva wawedzera kushandiswa.
Edzai nedata rinoenderana nemamiriro chaiwo ekugadzira.
Edzai nedata rinoenderana nemamiriro chaiwo ekugadzira. Bata nhanho yega yega segedhi rehumbowo: kana maitiro asina kusangana, imbomira kuburitsa, vhara gaka, uye wobva wawedzera kushandiswa.
Wedzera ongororo yemunhu kune yakaderera-kusavimbika kana yakakwirira-inokanganisa kufanotaura.
Wedzera ongororo yemunhu kune yakaderera-kusavimbika kana yakakwirira-inokanganisa kufanotaura. Bata nhanho yega yega segedhi rehumbowo: kana maitiro asina kusangana, imbomira kuburitsa, vhara gaka, uye wobva wawedzera kushandiswa.
Tevera modhi kudonha uye simbisa mushure mekuchinja kwekamera kana dataset.
Tevera modhi kudonha uye simbisa mushure mekuchinja kwekamera kana dataset. Bata nhanho yega yega segedhi rehumbowo: kana maitiro asina kusangana, imbomira kuburitsa, vhara gaka, uye wobva wawedzera kushandiswa.