{"id":90486,"date":"2025-03-04T16:47:55","date_gmt":"2025-03-04T08:47:55","guid":{"rendered":"https:\/\/solomon-3d.mesvr.tw\/?p=90486"},"modified":"2025-07-18T16:42:15","modified_gmt":"2025-07-18T08:42:15","slug":"rastgele-kutu-secimi-tam-kilavuzu","status":"publish","type":"post","link":"https:\/\/solomon-3d.mesvr.tw\/tr\/blog\/rastgele-kutu-secimi-tam-kilavuzu\/","title":{"rendered":"Rastgele Kutu Se\u00e7imi Tam K\u0131lavuzu"},"content":{"rendered":"
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Rastgele Kutu Se\u00e7imi Tam K\u0131lavuzu<\/h1><\/div>\n\n\n\n
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Rastgele Kutu Se\u00e7imi Nedir?<\/h2>\n\n\n\n
Rastgele kutu se\u00e7imi, bir robotun, 3D kamera yard\u0131m\u0131yla, rastgele d\u00fczenlenmi\u015f, bilinmeyen y\u00f6nelimlere ve d\u00fczensiz pozisyonlara sahip nesneleri bir kutudan veya konteynerden almas\u0131 i\u015flemi olarak tan\u0131mlan\u0131r. Bu s\u00fcre\u00e7 genellikle \u00fcretim ve depo ortamlar\u0131nda uygulan\u0131r ve temel amac\u0131, rastgele veya d\u00fczensiz bir y\u0131\u011f\u0131n i\u00e7inden \u00f6\u011felerin otomatik olarak al\u0131nmas\u0131n\u0131 sa\u011flamakt\u0131r.<\/div>\n<\/div>\n\n\n\n
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\"William<\/a><\/div>\n\n\n\n

William Lemus’tan uzman g\u00f6r\u00fc\u015fleri,
Yurtd\u0131\u015f\u0131 Saha Uygulama M\u00fchendisi M\u00fcd\u00fcr\u00fc,
Solomon Teknoloji \u015eirketi<\/strong><\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n <\/div><\/div>\n\n\n\n

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Rastgele Kutudan Se\u00e7me End\u00fcstrileri ve \u00d6rnekleri<\/h2>\n\n\n\n
Rastgele kutudan se\u00e7me, nesnelerin kutulardan veya konteynerlerden ayr\u0131lmas\u0131 ve s\u0131ralanmas\u0131n\u0131n tekrar eden, i\u015f g\u00fcc\u00fc yo\u011fun ve zaman al\u0131c\u0131 oldu\u011fu end\u00fcstrilerde \u00e7ok de\u011ferlidir. A\u015fa\u011f\u0131da \u00e7e\u015fitli sekt\u00f6rlerdeki \u00e7\u00f6p kutusu toplama uygulamalar\u0131ndan<\/a> birka\u00e7 \u00f6rnek verilmi\u015ftir.<\/div>\n\n\n\n
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Metal Nesnelerin Rastgele Kutudan Se\u00e7ilmesi<\/p>\n\n\n\n

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Lojistik<\/h3>\n\n\n\n
Lojistik ve depo y\u00f6netiminde<\/a>, rastgele kutudan se\u00e7me, kutularda rastgele konumland\u0131r\u0131lm\u0131\u015f pek \u00e7ok paketin s\u0131ralanmas\u0131 ve i\u015flenmesi i\u00e7in kullan\u0131l\u0131r. \u00d6rne\u011fin, k\u00fcresel bir e-ticaret platformu i\u00e7in yap\u0131lan bir projede, kar\u0131\u015f\u0131k paketler kutulardan se\u00e7ildi ve y\u00fcksek h\u0131zda bir konvey\u00f6r band\u0131na yerle\u015ftirildi. Ana zorluk, a\u011f\u0131r paketlerin g\u00fcvenli bir \u015fekilde i\u015flenerek hatal\u0131 i\u015fleme veya hasar riskini engelleyen y\u00fcksek h\u0131zda se\u00e7me oranlar\u0131n\u0131 s\u00fcrd\u00fcrmekti. Solomon\u2019un AI \u00e7\u00f6z\u00fcm\u00fc<\/a>, sistemin h\u0131zl\u0131 \u00e7al\u0131\u015fmas\u0131n\u0131 sa\u011flad\u0131, y\u00fcksek i\u015fleme taleplerini kar\u015f\u0131lad\u0131 ve farkl\u0131 paket boyutlar\u0131 ve a\u011f\u0131rl\u0131klar\u0131n\u0131 do\u011fru ve g\u00fcvenli bir \u015fekilde i\u015fledi.<\/div>\n<\/div>\n\n\n\n
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Otomotiv<\/h3>\n\n\n\n
Otomotiv end\u00fcstrisinde<\/a>, rastgele kutudan se\u00e7me, otomobil bile\u015fenlerinin i\u015flenmesi ve s\u0131ralanmas\u0131nda kullan\u0131l\u0131r. Kutudan se\u00e7me sistemlerinin ana zorlu\u011fu, her par\u00e7an\u0131n do\u011fru \u015fekilde s\u0131n\u0131fland\u0131r\u0131lmas\u0131, se\u00e7ilmesi ve d\u00fczg\u00fcn bir \u015fekilde istiflenmesini sa\u011flamak i\u00e7in y\u00fcksek do\u011fruluk elde etmektir. B\u00fcy\u00fck bir Japon otomobil \u00fcreticisi i\u00e7in yap\u0131lan bir projede, AccuPick<\/a>, otomobil par\u00e7alar\u0131n\u0131 do\u011fru bir \u015fekilde i\u015flemek i\u00e7in kullan\u0131ld\u0131. Bu sayede montaj ve yerle\u015ftirme hatalar\u0131 ve kusurlar\u0131n\u0131n \u00f6n\u00fcne ge\u00e7ilerek genel verimlilik art\u0131r\u0131ld\u0131.<\/div>\n<\/div>\n\n\n\n
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G\u0131da ve \u0130\u00e7ecek<\/h3>\n\n\n\n
G\u0131da end\u00fcstrisinde<\/a>, rastgele kutudan se\u00e7me, g\u0131da \u00fcr\u00fcnlerinin s\u0131ralanmas\u0131 ve i\u015flenmesinin otomatikle\u015ftirilmesinde \u00f6nemli bir rol oynamaktad\u0131r ve operasyonel verimlili\u011fi \u00f6nemli \u00f6l\u00e7\u00fcde art\u0131r\u0131r. Solomon\u2019un bu sekt\u00f6rdeki dikkat \u00e7ekici projelerinden biri, lider bir \u00e7ok uluslu \u015fekerleme \u015firketi ile yap\u0131lan i\u015fbirli\u011fiyle, paketlenmi\u015f kurabiyelerin kutulardan se\u00e7ilerek konvey\u00f6r band\u0131na aktar\u0131lmas\u0131yd\u0131. Ana zorluk, sistemin dakikada yakla\u015f\u0131k 30 ila 35 kurabiye se\u00e7ip yerle\u015ftirmesi gerekti\u011fi i\u00e7in d\u00f6ng\u00fc zaman\u0131n\u0131 optimize etmekti. Otomasyon, operat\u00f6rlerin fiziksel y\u00fck\u00fcn\u00fc azaltmak ve kas iskelet sistemi yaralanmalar\u0131n\u0131 en aza indirmek i\u00e7in uyguland\u0131, bu da nihayetinde hem i\u015f g\u00fcvenli\u011fini hem de \u00fcretim hatt\u0131 verimlili\u011fini art\u0131rd\u0131.<\/div>\n<\/div>\n\n\n\n
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\u00dcretim<\/h3>\n\n\n\n
BiKutudan se\u00e7me, \u00fcretimde<\/a> \u00e7e\u015fitli bile\u015fenleri se\u00e7mek ve s\u0131ralamak i\u00e7in yayg\u0131n olarak kullan\u0131l\u0131r. End\u00fcstriyel robotlar ve otomasyon makineleri \u00fcreten bir lider firma, belirli metal par\u00e7alar\u0131n y\u00fcksek h\u0131zda rastgele kutudan se\u00e7ilmesi i\u00e7in kutudan se\u00e7me i\u015flemi ger\u00e7ekle\u015ftirmek zorundayd\u0131. Ana zorluklar, s\u0131k\u0131 d\u00f6ng\u00fc zaman\u0131 ve do\u011fruluk gereksinimleriydi. Nesnelerin d\u00fc\u015f\u00fc\u015f istasyonunda istiflenmesi gerekti\u011fi i\u00e7in herhangi bir se\u00e7im hatas\u0131, yanl\u0131\u015f istiflemeye yol a\u00e7ard\u0131. Nesneler \u00fcstten veya arkadan bir bak\u0131\u015f a\u00e7\u0131s\u0131yla yerle\u015ftirilebiliyordu, de\u011fi\u015fken e\u011fim a\u00e7\u0131lar\u0131yla, bu da AI’n\u0131n her y\u00fcz\u00fc ve a\u00e7\u0131y\u0131 do\u011fru \u015fekilde tespit etmesini gerektiriyordu. Metal nesnelerin parlak y\u00fczeyi, 3D kameralar i\u00e7in \u0131\u015f\u0131k yans\u0131mas\u0131 nedeniyle ek bir zorluk olu\u015fturuyordu. Bu yans\u0131ma, hem 2D g\u00f6r\u00fcnt\u00fc hem de 3D nokta bulutunu bozarak se\u00e7im do\u011frulu\u011funu d\u00fc\u015f\u00fcrebiliyordu. Bu sorunu a\u015fmak i\u00e7in, SolScan end\u00fcstriyel 3D kamera<\/a>, genellikle kullan\u0131lan beyaz \u0131\u015f\u0131k yerine ye\u015fil projekt\u00f6r \u0131\u015f\u0131\u011f\u0131 ile donat\u0131ld\u0131.<\/div>\n\n\n\n
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Orijinal 2D G\u00f6r\u00fcnt\u00fc<\/p>\n<\/div>\n\n\n\n

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2D AI Alg\u0131lama ile A\u00e7\u0131 Tan\u0131ma<\/p>\n<\/div>\n\n\n\n

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3D Nokta Bulutu ile Se\u00e7im Noktas\u0131 Yerle\u015ftirilmesi<\/p>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n

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\u0130la\u00e7 ve Medikal<\/h3>\n\n\n\n
\u0130la\u00e7 ve medikal end\u00fcstrisinde, \u00e7\u00f6p toplama si\u0307stemleri\u0307<\/a>, y\u00fcksek h\u0131zl\u0131 ortamlarda \u00e7e\u015fitli \u00f6\u011feleri hassasiyetle y\u00f6netmek i\u00e7in hayati \u00f6neme sahiptir. Bu durumda, bir ila\u00e7 da\u011f\u0131t\u0131c\u0131s\u0131, farkl\u0131 \u015fekil, boyut ve renklere sahip kutular ve \u015fi\u015feler dahil olmak \u00fczere \u00e7e\u015fitli konteynerleri, her bin i\u00e7inde yakla\u015f\u0131k be\u015f \u00f6\u011fe rastgele konumland\u0131r\u0131lm\u0131\u015f ve y\u00f6nlendirilmi\u015f olarak y\u00f6netiyordu. Ana zorluk, \u00fcr\u00fcn\u00fcn barkodunun al\u0131m s\u0131ras\u0131nda g\u00f6r\u00fcn\u00fcr oldu\u011fundan emin olmakt\u0131, \u00e7\u00fcnk\u00fc \u00f6\u011feler barkod okuyucular\u0131 aras\u0131nda yerle\u015ftirilerek tarama yap\u0131lmas\u0131 gerekiyordu. \u00c7al\u0131\u015fma alan\u0131 s\u0131n\u0131rl\u0131yd\u0131 ve robotlar, kat\u0131 d\u00f6ng\u00fc s\u00fcrelerini kar\u015f\u0131lamak i\u00e7in y\u00fcksek h\u0131zda \u00e7al\u0131\u015fmak zorunda kald\u0131\u011f\u0131ndan, \u00e7arp\u0131\u015fma riski art\u0131yordu. Bu sorunu \u00e7\u00f6zmek i\u00e7in AccuPick<\/a> kullan\u0131ld\u0131. Hareket planlama yaz\u0131l\u0131m\u0131, g\u00fcvenli ve \u00e7arp\u0131\u015fmas\u0131z yollar hesaplad\u0131, ayr\u0131ca yerle\u015fik AI, y\u00fcksek do\u011frulukta alg\u0131lama yaparak robotun \u00f6\u011feleri herhangi bir pozisyondan (\u00fcst, yan veya alt) almas\u0131n\u0131 sa\u011flad\u0131 ve barkodu engellemeden al\u0131m yapt\u0131. \u0130ki farkl\u0131 robot u\u00e7 etkileyici\u2014biri b\u00fcy\u00fck bir emi\u015f pedi, di\u011feri k\u00fc\u00e7\u00fck bir emi\u015f pediyle\u2014kullan\u0131ld\u0131 ve nesne alg\u0131lama sonu\u00e7lar\u0131na, konum ve t\u00fcr\u00fcne (kutular veya \u015fi\u015feler) dayanarak stratejik ko\u015fullar ve kurallar olu\u015fturuldu, b\u00f6ylece her bir \u00f6zel nesne durumu i\u00e7in uygun u\u00e7 etkileyici se\u00e7ildi.<\/div>\n<\/div>\n<\/div>\n <\/div><\/div>\n\n\n\n
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Daha fazla end\u00fcstriyel \u00e7\u00f6p kutusu toplama \u00f6rne\u011fi ke\u015ffedin<\/span><\/span><\/span><\/a><\/div>\n<\/div>\n <\/div><\/div>\n\n\n\n
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Rastgele Bin Picking Sistemi Temel Unsurlar\u0131<\/h2>\n\n\n\n
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Ara\u00e7 Merkez Noktas\u0131 (TCP) Kalibrasyonu<\/h3>\n\n\n\n
Robotun u\u00e7 efekt\u00f6r\u00fc uygulama i\u00e7in se\u00e7ildikten ve robotun flan\u015f\u0131na monte edildikten sonra TCP kalibrasyonu yap\u0131lmal\u0131d\u0131r. TCP, robotun u\u00e7 efekt\u00f6r\u00fcn\u00fcn do\u011fru pozisyonu ve y\u00f6n\u00fc hakk\u0131nda talimatlar vermek i\u00e7in referans noktas\u0131 olarak kullan\u0131l\u0131r.<\/div>\n\n\n\n
\"Diagram<\/div>\n\n\n\n

TCP Kalibrasyonu<\/p>\n<\/div>\n\n\n\n

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G\u00f6r\u00fc\u015f Sistemi ile Robot Kalibrasyonu<\/h3>\n\n\n\n
G\u00f6r\u00fc\u015f sistemi<\/a> ile robot aras\u0131nda kalibrasyon yapmak \u00e7ok \u00f6nemlidir. 3D kameran\u0131n koordinat ba\u015flang\u0131c\u0131 kameran\u0131n taban\u0131nda bulunurken, robotun koordinat ba\u015flang\u0131c\u0131 robotun taban\u0131nda yer almaktad\u0131r. Kalibrasyon, robotun kameran\u0131n koordinat sistemini anlamas\u0131n\u0131 ve bu koordinatlar\u0131 kendi koordinat sistemine d\u00f6n\u00fc\u015ft\u00fcrmesini sa\u011flar. Sonu\u00e7 olarak, 3D taray\u0131c\u0131dan robotuna g\u00f6nderilen herhangi bir pozisyonel ve d\u00f6n\u00fc\u015fsel koordinat do\u011fru bir \u015fekilde yorumlan\u0131r ve robotun istenilen pozisyon ve d\u00f6n\u00fc\u015fle belirli bir noktaya ula\u015fmas\u0131 sa\u011flan\u0131r.<\/div>\n\n\n\n
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3D Tarama ve Nesne Alg\u0131lama<\/h3>\n\n\n\n
3D taray\u0131c\u0131, bin i\u00e7indeki nesnelerin hem 2D g\u00f6r\u00fcnt\u00fclerini hem de 3D nokta bulutlar\u0131n\u0131 yakalar. Bu veriler, al\u0131m i\u00e7in temel kriterlere uyan nesneler i\u00e7in bir al\u0131m noktas\u0131 olu\u015fturmak amac\u0131yla kullan\u0131l\u0131r. Bu kriterler projeye g\u00f6re de\u011fi\u015febilir, ancak genel olarak \u015funlar\u0131 i\u00e7erir:

\u2022 Bin’in \u00fcst y\u00fczeyinde bulunan nesneler.

\u2022 Di\u011fer \u00f6\u011feler taraf\u0131ndan engellenmeyen veya yaln\u0131zca hafif\u00e7e engellenmi\u015f olan nesneler.

\u2022 Nesnenin al\u0131m y\u00f6n\u00fcn\u00fc belirlemeye yard\u0131mc\u0131 olan g\u00f6r\u00fcn\u00fcr \u00f6zellikler.

\u2022 Nesneler g\u00fcvenli bir \u015fekilde konumland\u0131r\u0131lm\u0131\u015f ve d\u00f6nd\u00fcr\u00fclm\u00fc\u015f olmal\u0131d\u0131r, b\u00f6ylece robot veya u\u00e7 efekt\u00f6r\u00fc al\u0131m s\u0131ras\u0131nda \u00e7arp\u0131\u015fma yapmaz.<\/div>\n\n\n\n
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Al\u0131m Noktas\u0131 Olu\u015fumu ve Uygulama<\/h3>\n\n\n\n
Her nesne i\u00e7in al\u0131m noktas\u0131 genellikle hem pozisyonel hem de d\u00f6n\u00fc\u015fsel koordinatlar\u0131 i\u00e7erir. Al\u0131m noktas\u0131 olu\u015fturulduktan sonra, robot bu al\u0131m noktas\u0131n\u0131 al\u0131r. Ard\u0131ndan robot kontrol\u00f6r\u00fc, bu noktaya ula\u015fmak i\u00e7in yolu hesaplar. \u00c7arp\u0131\u015fma \u00f6ncesi ortamlarda daha zor uygulamalar i\u00e7in, g\u00fcvenli bir yol hesaplamak ad\u0131na hareket planlama yaz\u0131l\u0131m\u0131 gereklidir. Al\u0131m noktas\u0131na ula\u015f\u0131ld\u0131\u011f\u0131nda, robot nesneyi al\u0131r ve ard\u0131ndan istenilen konum veya bin’e b\u0131rak\u0131r.<\/div>\n\n\n\n
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D\u00f6ng\u00fc Tekrar\u0131<\/h3>\n\n\n\n
Mevcut d\u00f6ng\u00fcdeki t\u00fcm alg\u0131lanan nesneler al\u0131n\u0131p b\u0131rak\u0131ld\u0131ktan sonra, yeni bir d\u00f6ng\u00fc tarama ad\u0131m\u0131ndan ba\u015flar. Bu, bin bo\u015falana kadar kesintisiz \u00e7al\u0131\u015fmay\u0131 sa\u011flar.<\/div>\n\n\n\n
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Solomon’un 3D \u00e7\u00f6p kutusu toplama sistemi hakk\u0131nda bilgi edinin<\/span><\/span><\/span><\/a><\/div>\n<\/div>\n <\/div><\/div>\n\n\n\n
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Rastgele Bin Picking Zorluklar\u0131 ve \u00c7\u00f6z\u00fcmleri<\/h2>\n\n\n\n
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S\u0131k\u0131 D\u00f6ng\u00fc Zaman\u0131 Gereksinimleri<\/h3>\n\n\n\n
S\u0131k\u0131 d\u00f6ng\u00fc zaman\u0131 gereksinimleri olan projeler, her ad\u0131m\u0131n h\u0131zla tamamlanmas\u0131 gerekti\u011finden \u00f6nemli zorluklarla kar\u015f\u0131la\u015f\u0131r. Anahtar fakt\u00f6rler \u015funlard\u0131r:

\u2022\u00a03D Kamera \u00c7ekim S\u00fcresi:<\/strong> 3D kamera, hem 2D g\u00f6r\u00fcnt\u00fcleri hem de 3D nokta bulutlar\u0131n\u0131 h\u0131zl\u0131 bir \u015fekilde yakalamal\u0131d\u0131r.

\u2022\u00a0G\u00f6r\u00fcnt\u00fc ve Nokta Bulutu Olu\u015fumu:<\/strong> 2D g\u00f6r\u00fcnt\u00fcleri ve 3D nokta bulutlar\u0131n\u0131 olu\u015fturacak algoritmalar verimli ve optimize edilmi\u015f olmal\u0131d\u0131r.

\u2022\u00a0Nesne Tan\u0131mlama: <\/strong>Nesne tan\u0131mlama algoritmas\u0131 h\u0131zl\u0131 olmal\u0131d\u0131r; burada KI, h\u0131z ve do\u011frulu\u011fu b\u00fcy\u00fck \u00f6l\u00e7\u00fcde art\u0131rabilir.

\u2022\u00a0Al\u0131m Noktas\u0131 Yerle\u015ftirme:<\/strong> Al\u0131m noktalar\u0131n\u0131 belirleme algoritmas\u0131 h\u0131zl\u0131 olmal\u0131d\u0131r. Burada da KI kullan\u0131larak y\u00fcksek h\u0131z elde edilebilir.

\u2022\u00a0Hareket Planlamas\u0131:<\/strong> Hareket planlama sistemi g\u00fcvenli yollar\u0131 h\u0131zl\u0131ca hesaplamal\u0131d\u0131r.

\u2022\u00a0Robot H\u0131z\u0131: <\/strong>Robot, d\u00f6ng\u00fc zaman\u0131 taleplerini kar\u015f\u0131lamak i\u00e7in y\u00fcksek h\u0131zda \u00e7al\u0131\u015fmal\u0131d\u0131r.

\u2022\u00a0Sonland\u0131r\u0131c\u0131 Se\u00e7imi: <\/strong>Uygun sonland\u0131r\u0131c\u0131y\u0131 se\u00e7mek, ba\u015far\u0131s\u0131z se\u00e7imleri minimize etmek ve nesnelerin robot hareketleri s\u0131ras\u0131nda g\u00fcvenli bir \u015fekilde tutularak ta\u015f\u0131nmas\u0131n\u0131 sa\u011flamak i\u00e7in kritik \u00f6neme sahiptir.<\/div>\n\n\n\n
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Y\u00fcksek Se\u00e7im Do\u011frulu\u011fu<\/h3>\n\n\n\n
Y\u00fcksek se\u00e7im do\u011frulu\u011fu, etkili rastgele kutudan se\u00e7im i\u00e7in \u00e7ok \u00f6nemlidir. Anahtar hususlar \u015funlard\u0131r:

\u2022\u00a0Uygun 3D Taray\u0131c\u0131:<\/strong> Nesne malzemesi, \u00e7al\u0131\u015fma mesafesi ve kutu boyutlar\u0131 i\u00e7in uygun bir 3D taray\u0131c\u0131 se\u00e7mek \u00f6nemlidir.

\u2022\u00a0Y\u00fcksek \u00c7\u00f6z\u00fcn\u00fcrl\u00fck: <\/strong>3D taray\u0131c\u0131, ayr\u0131nt\u0131l\u0131 yakalama i\u00e7in y\u00fcksek \u00e7\u00f6z\u00fcn\u00fcrl\u00fck sunmal\u0131d\u0131r.

\u2022\u00a0Bilgisayarla G\u00f6r\u00fcnt\u00fcleme ve G\u00f6r\u00fcnt\u00fc \u0130\u015fleme: <\/strong>Geli\u015fmi\u015f bilgisayarla g\u00f6r\u00fcnt\u00fcleme teknikleri ve g\u00f6r\u00fcnt\u00fc i\u015fleme, do\u011frulu\u011fu \u00f6nemli \u00f6l\u00e7\u00fcde art\u0131rabilir.

\u2022\u00a0Nesne Tespiti \u0130\u00e7in AI:<\/strong> Do\u011fru AI algoritmas\u0131n\u0131 se\u00e7mek, nesne tespiti do\u011frulu\u011funu iyile\u015ftirebilir.

\u2022\u00a0Se\u00e7im Noktas\u0131 Yerle\u015ftirme \u0130\u00e7in AI: <\/strong>AI 3D e\u015fle\u015ftirme y\u00f6ntemleri, se\u00e7im noktas\u0131 yerle\u015ftirmesinin do\u011frulu\u011funu daha da iyile\u015ftirebilir.

\u2022\u00a0\u0130nce Ayar:<\/strong> 3D taray\u0131c\u0131 parametrelerinin, g\u00f6r\u00fcnt\u00fc i\u015fleme tekniklerinin, 2D tespit AI algoritmas\u0131n\u0131n ve se\u00e7im noktas\u0131 yerle\u015ftirme i\u00e7in 3D e\u015fle\u015ftirme y\u00f6nteminin kapsaml\u0131 ince ayarlar\u0131, optimal performans i\u00e7in gereklidir.

\u2022\u00a0Stabil Ayd\u0131nlatma Ortam\u0131: <\/strong>Tutarl\u0131 sonu\u00e7lar elde etmek i\u00e7in stabil bir ayd\u0131nlatma ortam\u0131n\u0131n sa\u011flanmas\u0131 \u00f6nemlidir.<\/div>\n\n\n\n
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Rastgele Nesne Y\u00f6nelimi<\/h3>\n\n\n\n
Kutulardaki nesneler genellikle rastgele d\u00fczenlenmi\u015f, bilinmeyen y\u00f6nelimlerde ve d\u00fczensiz pozisyonlarda olur. Bu rastgelelik, nesnelerin birbiriyle engellenmesine yol a\u00e7abilir. Bu zorluklar\u0131n \u00fcstesinden gelmek i\u00e7in \u00e7e\u015fitli stratejiler uygulanabilir:

\u2022\u00a0Katman Katman Yakla\u015f\u0131m\u0131:<\/strong> En uygun nesneleri taray\u0131n ve se\u00e7in, ard\u0131ndan bir sonraki iterasyonu ba\u015flatmak i\u00e7in yeniden taray\u0131n, katman katman ilerleyin.

\u2022\u00a0Kutu \u00c7alkalay\u0131c\u0131:<\/strong> Nesnelerin pozisyonlar\u0131n\u0131 de\u011fi\u015ftirmek i\u00e7in bir kutu \u00e7alkalay\u0131c\u0131 kullan\u0131n.

\u2022\u00a0\u0130ki A\u015famal\u0131 Se\u00e7im:<\/strong> \u0130lk olarak, nesneyi m\u00fcmk\u00fcn oldu\u011funca etkili bir \u015fekilde se\u00e7in, ard\u0131ndan daha do\u011fru al\u0131m i\u00e7in nesneleri di\u011fer nesnelerden ay\u0131rarak ikincil bir istasyonda i\u015flem yap\u0131n.

\u2022\u00a0Sonland\u0131r\u0131c\u0131:<\/strong> Uygun sonland\u0131r\u0131c\u0131y\u0131 se\u00e7mek, zorlu senaryolarda nesnelerin ba\u015far\u0131yla se\u00e7ilme olas\u0131l\u0131\u011f\u0131n\u0131 art\u0131rmak i\u00e7in \u00e7ok \u00f6nemlidir.

\u2022\u00a0Kutu Tasar\u0131m\u0131:<\/strong> Kutunun tasar\u0131m\u0131 kritik \u00f6neme sahiptir. Belirli uygulamalar i\u00e7in tersine koni \u015feklinde bir kutu tasar\u0131m\u0131 etkili bir \u00e7\u00f6z\u00fcm sunabilir.<\/div>\n\n\n\n
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Eksik Se\u00e7im Do\u011frulu\u011fu<\/h3>\n\n\n\n
Geli\u015fmi\u015f g\u00f6rsel sistemlerin<\/a> yeteneklerine ra\u011fmen, se\u00e7im do\u011frulu\u011fu her zaman %100 olmayabilir. Kutunun alt k\u0131sm\u0131nda, kenarlarda veya k\u00f6\u015felerde konumlanm\u0131\u015f nesneler, yerlerinden dolay\u0131 se\u00e7ilmemi\u015f olabilir. Bu durumlarda, nesneleri daha eri\u015filebilir alanlara yeniden konumland\u0131rmak i\u00e7in bir kutu \u00e7alkalay\u0131c\u0131 kullanmak etkili bir \u00e7\u00f6z\u00fcm olabilir.<\/div>\n\n\n\n
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S\u0131n\u0131rl\u0131 \u00c7al\u0131\u015fma Alan\u0131 ve Y\u00fcksek Robot H\u0131z\u0131<\/h3>\n\n\n\n
S\u0131n\u0131rl\u0131 alanlarda, y\u00fcksek h\u0131zda robot hareketi gerekliyse, hareket planlama yaz\u0131l\u0131m\u0131 gereklidir. \u00c7al\u0131\u015fma alan\u0131 ve sonland\u0131r\u0131c\u0131 i\u00e7in hafif bir CAD dosyas\u0131 gerekebilir, bu dosya robot modelini i\u00e7ermeli ve potansiyel rotalar\u0131 sim\u00fcle ederek en g\u00fcvenli yolu hesaplamal\u0131d\u0131r.<\/div>\n\n\n\n
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\u015eeffaf veya Parlak Nesneler<\/h3>\n\n\n\n
\u015eeffaf veya parlak metal nesneler, se\u00e7im noktas\u0131 yerle\u015ftirme i\u00e7in do\u011fru bir nokta bulutu \u00fcretme konusunda ek zorluklar yaratabilir. \u00c7\u00f6z\u00fcmler aras\u0131nda AI, bilgisayarla g\u00f6r\u00fcnt\u00fcleme ve g\u00f6r\u00fcnt\u00fc i\u015fleme tekniklerinin uygulanmas\u0131, ayr\u0131ca y\u00fcksek kaliteli 3D taray\u0131c\u0131lar\u0131n <\/a>kullan\u0131lmas\u0131 yer al\u0131r. Stereo g\u00f6r\u00fcnt\u00fcleme ve yap\u0131sal projekt\u00f6r \u0131\u015f\u0131\u011f\u0131 gibi y\u00f6ntemlerin birle\u015ftirilmesi, farkl\u0131 \u0131\u015f\u0131k renkleri, y\u00fcksek \u00e7\u00f6z\u00fcn\u00fcrl\u00fck ve artt\u0131r\u0131lm\u0131\u015f \u0131\u015f\u0131k yo\u011funlu\u011fu ile bu zorluklar\u0131n \u00fcstesinden gelmek m\u00fcmk\u00fcnd\u00fcr.<\/div>\n\n\n\n
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\"semi-transparent<\/figure>\n<\/div>\n\n\n

Case Study: Yar\u0131 Saydam \u00dcr\u00fcnler<\/a><\/strong><\/p>\n<\/div>\n\n\n\n

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\"Shiny<\/figure>\n<\/div>\n\n\n

Case Study: Parlak Metal Par\u00e7alar<\/a><\/strong><\/p>\n<\/div>\n<\/div>\n<\/div>\n <\/div><\/div>\n\n\n\n

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Yapay Zeka Kullanarak Rastgele Kutu Se\u00e7me<\/h2>\n\n\n\n
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Yapay Zeka (AI)<\/a>, y\u00fcksek kaliteli tespit ve do\u011fru al\u0131m noktas\u0131 yerle\u015ftirmeyi sa\u011flarken end\u00fcstriyel uygulamalarda rekabet\u00e7i d\u00f6ng\u00fc s\u00fcrelerini korumada \u00f6nemli bir rol oynar. Bilgisayarla g\u00f6rme ve g\u00f6r\u00fcnt\u00fc \u00f6n i\u015fleme teknikleriyle birle\u015fti\u011finde, AI, \u00e7e\u015fitli \u00e7evresel ko\u015fullara ve nesne y\u00f6nelimlerine uyum sa\u011flayabilir. Bu uyum sa\u011flama yetene\u011fi, nesnelerin rastgele yerle\u015ftirildi\u011fi rastgele kutudan alma uygulamalar\u0131 i\u00e7in AI\u2019yi \u00f6zellikle uygun hale getirir. Bu senaryolar i\u00e7in geli\u015ftirilen AI modelleri, g\u00fc\u00e7l\u00fc ve esnek olmal\u0131, farkl\u0131 al\u0131m zorluklar\u0131yla ba\u015fa \u00e7\u0131kabilmelidir.<\/div>\n\n\n\n
\"Automated<\/a><\/div>\n\n\n\n
AI ve geli\u015fmi\u015f g\u00f6rsel sistemlerle desteklenen rastgele kutudan alma, farkl\u0131 sekt\u00f6rlerde end\u00fcstriyel otomasyonu d\u00f6n\u00fc\u015ft\u00fcr\u00fcyor. Solomon\u2019un AI ve 3D g\u00f6rsel \u00e7\u00f6z\u00fcmleri<\/a> ile operasyonlar\u0131n\u0131z\u0131 nas\u0131l optimize edebilece\u011finizi ke\u015ffedin.<\/strong><\/div>\n<\/div>\n<\/div>\n <\/div><\/div>\n\n\n\n
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AccuPick ile yapay zeka tabanl\u0131 \u00e7\u00f6p toplama hakk\u0131nda daha fazla bilgi edinin<\/span><\/span><\/span><\/a><\/div>\n<\/div>\n <\/div><\/div>","protected":false},"excerpt":{"rendered":"

Sistem temelleri, sekt\u00f6r \u00f6rnekleri, kar\u015f\u0131la\u015f\u0131lan zorluklar ve yapay zeka destekli \u00e7\u00f6z\u00fcmler hakk\u0131nda uzman g\u00f6r\u00fc\u015fleri i\u00e7eren kapsaml\u0131 rastgele \u00e7\u00f6p kutusu toplama k\u0131lavuzumuzu ke\u015ffedin.<\/p>","protected":false},"author":875,"featured_media":61737,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_gspb_post_css":"#gspb_row-id-gsbp-5aebb46{justify-content:space-between;margin-top:0;margin-bottom:0;display:flex;flex-wrap:wrap;min-height:250px;padding:0;overflow:hidden;background-size:cover;background-repeat:no-repeat;background-position:50% 68%;background-image:url(https:\/\/solomon-3d.mesvr.tw\/wp-content\/uploads\/2024\/01\/\u2014Pngtree\u2014technological-sense-geometric-line-simple_932581-1.jpg);filter:brightness(1) contrast(1) 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