{"id":1822,"date":"2026-05-14T09:52:49","date_gmt":"2026-05-14T09:52:49","guid":{"rendered":"https:\/\/hria.utcluj.ro\/?p=1822"},"modified":"2026-05-14T09:52:51","modified_gmt":"2026-05-14T09:52:51","slug":"sisteme-avansate-de-robotica-medicala-localizarea-athena-estimarea-fortei-sensorless-si-navigatie-dentara-markerless","status":"publish","type":"post","link":"https:\/\/hria.utcluj.ro\/en\/sisteme-avansate-de-robotica-medicala-localizarea-athena-estimarea-fortei-sensorless-si-navigatie-dentara-markerless\/","title":{"rendered":"Sisteme avansate de robotic\u0103 medical\u0103: localizarea ATHENA, estimarea for\u021bei sensorless \u0219i naviga\u021bie dentar\u0103 markerless"},"content":{"rendered":"<p class=\"wp-block-paragraph\">Cercet\u0103rile vizeaz\u0103 g\u0103sirea de solu\u021bii inovatoare pentru chirurgia minim invaziv\u0103 \u0219i implantologia robotizat\u0103, elimin\u00e2nd necesitatea senzorilor hardware complec\u0219i prin utilizarea tehnicilor avansate de Computer Vision.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Localizarea \u0219i pozi\u021bionarea automat\u0103 a robotului ATHENA<\/strong><\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Obiectiv:<\/strong> Realizarea unei localiz\u0103ri 3D \u00een timp real, f\u0103r\u0103 markeri fizici, pentru a permite andocarea automat\u0103 \u0219i pentru a reduce variabilitatea configur\u0103rii. Sistemul prime\u0219te date de la o camer\u0103 RGB-D.<\/li>\n\n\n\n<li><strong>Arhitectur\u0103 de detec\u021bie:<\/strong> S-a utilizat modelul <strong>YOLO11m<\/strong> (ales \u00een defavoarea versiunilor YOLO8m\/9m\/10m) pentru detec\u021bia a 3 clase specifice: trocarul, instrumentul laparoscopic \u0219i modulul paralel (PM) al robotului.<\/li>\n\n\n\n<li><strong>Estimare 3D:<\/strong> Sistemul converte\u0219te coordonatele pixelilor din bounding box-urile 2D \u0219i informa\u021bia de ad\u00e2ncime (depth) \u00een coordonate 3D pentru componentele cheie.<\/li>\n\n\n\n<li><strong>Performan\u021b\u0103 \u0219i laten\u021b\u0103:<\/strong> Evaluarea a indicat un mAP de aproximativ 0.9947, o precizie de 0.9879 \u0219i un recall de 0.9849. Laten\u021ba de inferen\u021b\u0103 este de aproximativ 14.7 ms, cu o laten\u021b\u0103 end-to-end de aproximativ 67 ms.<\/li>\n\n\n\n<li><strong>Impact:<\/strong> Solu\u021bia ob\u021bine o pozi\u021bionare cu o marj\u0103 de eroare de $\\le 0.8$ mm \u0219i asigur\u0103 o reducere de 42% a timpului de setup comparativ cu alinierea manual\u0103.<\/li>\n<\/ul>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-full is-resized\"><img fetchpriority=\"high\" decoding=\"async\" width=\"839\" height=\"753\" src=\"https:\/\/hria.utcluj.ro\/wp-content\/uploads\/2026\/05\/localization-ATHENA.png\" alt=\"\" class=\"wp-image-1828\" style=\"width:547px;height:auto\" srcset=\"https:\/\/hria.utcluj.ro\/wp-content\/uploads\/2026\/05\/localization-ATHENA.png 839w, https:\/\/hria.utcluj.ro\/wp-content\/uploads\/2026\/05\/localization-ATHENA-300x269.png 300w, https:\/\/hria.utcluj.ro\/wp-content\/uploads\/2026\/05\/localization-ATHENA-768x689.png 768w, https:\/\/hria.utcluj.ro\/wp-content\/uploads\/2026\/05\/localization-ATHENA-13x12.png 13w\" sizes=\"(max-width: 839px) 100vw, 839px\" \/><figcaption class=\"wp-element-caption\">Ahitectura solu\u021biei propuse: de la achizi\u021bia datelor la controlul mi\u0219c\u0103rii robotului<\/figcaption><\/figure>\n<\/div>\n\n\n<div class=\"wp-block-columns is-layout-flex wp-container-core-columns-is-layout-8f761849 wp-block-columns-is-layout-flex\">\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\"><div class=\"wp-block-image\">\n<figure class=\"aligncenter size-full is-resized\"><img decoding=\"async\" width=\"766\" height=\"628\" src=\"https:\/\/hria.utcluj.ro\/wp-content\/uploads\/2026\/05\/instrument-detection.png\" alt=\"\" class=\"wp-image-1829\" style=\"aspect-ratio:1.2197647058823529;width:526px;height:auto\" srcset=\"https:\/\/hria.utcluj.ro\/wp-content\/uploads\/2026\/05\/instrument-detection.png 766w, https:\/\/hria.utcluj.ro\/wp-content\/uploads\/2026\/05\/instrument-detection-300x246.png 300w, https:\/\/hria.utcluj.ro\/wp-content\/uploads\/2026\/05\/instrument-detection-15x12.png 15w\" sizes=\"(max-width: 766px) 100vw, 766px\" \/><figcaption class=\"wp-element-caption\">Detec\u021bia instrumentelor<\/figcaption><\/figure>\n<\/div><\/div>\n\n\n\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\"><div class=\"wp-block-image\">\n<figure class=\"aligncenter size-full\"><img decoding=\"async\" width=\"776\" height=\"585\" src=\"https:\/\/hria.utcluj.ro\/wp-content\/uploads\/2026\/05\/ATHENA-parallel-robot.png\" alt=\"\" class=\"wp-image-1830\" srcset=\"https:\/\/hria.utcluj.ro\/wp-content\/uploads\/2026\/05\/ATHENA-parallel-robot.png 776w, https:\/\/hria.utcluj.ro\/wp-content\/uploads\/2026\/05\/ATHENA-parallel-robot-300x226.png 300w, https:\/\/hria.utcluj.ro\/wp-content\/uploads\/2026\/05\/ATHENA-parallel-robot-768x579.png 768w, https:\/\/hria.utcluj.ro\/wp-content\/uploads\/2026\/05\/ATHENA-parallel-robot-16x12.png 16w\" sizes=\"(max-width: 776px) 100vw, 776px\" \/><figcaption class=\"wp-element-caption\">Robotul paralel ATHENA<\/figcaption><\/figure>\n<\/div><\/div>\n<\/div>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Estimarea for\u021bei \u201esensorless\u201d \u00een chirurgia minim invaziv\u0103<\/strong><\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Obiectiv:<\/strong> Estimarea for\u021bei de interac\u021biune instrument-\u021besut exclusiv din date video, elimin\u00e2nd necesitatea unui senzor distal. Intrarea const\u0103 \u00eentr-un singur cadru endoscopic RGB.<\/li>\n\n\n\n<li><strong>Model:<\/strong> O re\u021bea CNN u\u0219oar\u0103, bazat\u0103 pe <strong>EfficientNetV2B0<\/strong>, adaptat\u0103 pentru regresia for\u021bei pentru a oferi o singur\u0103 ie\u0219ire scalar\u0103 \u00een Newtoni.<\/li>\n\n\n\n<li><strong>Set de date:<\/strong> Antrenamentul s-a bazat pe 40 de clipuri video (9691 de cadre etichetate) ob\u021binute din teste in vitro pe esofag, cu etichete de for\u021b\u0103 \u00een intervalul 0-5 N. Ground-truth-ul a fost preluat de la un senzor Robotiq FT300 montat pe un robot KUKA iiwa LBR 7 R800.<\/li>\n\n\n\n<li><strong>Performan\u021b\u0103 tehnic\u0103:<\/strong> Modelul raporteaz\u0103 o eroare medie absolut\u0103 (MAE) de 0.017 N \u0219i o eroare p\u0103tratic\u0103 medie (MSE) de 0.0004 N\u00b2.<\/li>\n\n\n\n<li><strong>Deployment:<\/strong> Inferen\u021ba dureaz\u0103 aproximativ 12.34 ms, func\u021bion\u00e2nd la o rat\u0103 de actualizare de aproximativ 6 Hz, cu o laten\u021b\u0103 de predic\u021bie de 15-20 ms.<\/li>\n\n\n\n<li><strong>Integrare hardware:<\/strong> Algoritmul opereaz\u0103 ca plug-in pe platforma PARA-SILSROB \u0219i controleaz\u0103 un dispozitiv haptic Force Dimension Omega.7.<\/li>\n<\/ul>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"624\" src=\"https:\/\/hria.utcluj.ro\/wp-content\/uploads\/2026\/05\/force-feedback-architecture-1-1024x624.png\" alt=\"\" class=\"wp-image-1825\" srcset=\"https:\/\/hria.utcluj.ro\/wp-content\/uploads\/2026\/05\/force-feedback-architecture-1-1024x624.png 1024w, https:\/\/hria.utcluj.ro\/wp-content\/uploads\/2026\/05\/force-feedback-architecture-1-300x183.png 300w, https:\/\/hria.utcluj.ro\/wp-content\/uploads\/2026\/05\/force-feedback-architecture-1-768x468.png 768w, https:\/\/hria.utcluj.ro\/wp-content\/uploads\/2026\/05\/force-feedback-architecture-1-18x12.png 18w, https:\/\/hria.utcluj.ro\/wp-content\/uploads\/2026\/05\/force-feedback-architecture-1.png 1161w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><figcaption class=\"wp-element-caption\">Modelul  <strong>EfficientNetV2B0<\/strong> pentru estimarea for\u021bei<\/figcaption><\/figure>\n<\/div>\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-full is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"890\" height=\"452\" src=\"https:\/\/hria.utcluj.ro\/wp-content\/uploads\/2026\/05\/force-feedback-robot-1.png\" alt=\"\" class=\"wp-image-1826\" style=\"width:656px;height:auto\" srcset=\"https:\/\/hria.utcluj.ro\/wp-content\/uploads\/2026\/05\/force-feedback-robot-1.png 890w, https:\/\/hria.utcluj.ro\/wp-content\/uploads\/2026\/05\/force-feedback-robot-1-300x152.png 300w, https:\/\/hria.utcluj.ro\/wp-content\/uploads\/2026\/05\/force-feedback-robot-1-768x390.png 768w, https:\/\/hria.utcluj.ro\/wp-content\/uploads\/2026\/05\/force-feedback-robot-1-18x9.png 18w\" sizes=\"(max-width: 890px) 100vw, 890px\" \/><figcaption class=\"wp-element-caption\">Robotul chirurgical PARA-SILSROB<\/figcaption><\/figure>\n<\/div>\n\n\n<h3 class=\"wp-block-heading\"><strong>Percep\u021bie <strong>\u201e<\/strong>markerless<strong>\u201d<\/strong> pentru naviga\u021bia \u00een implantologia dentar\u0103<\/strong><\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Naviga\u021bie dinamic\u0103 \u0219i control (obiectiv 1):<\/strong> Sistemul folose\u0219te un detector YOLO antrenat pe 752 de imagini intraorale pentru a identifica repere anatomice. Aceast\u0103 detec\u021bie atinge o precizie de 91.2%, recall de 88.5% \u0219i mAP@0.5 de 91.2%.<\/li>\n\n\n\n<li><strong>Aliniere \u0219i arhitectur\u0103:<\/strong> Se utilizeaz\u0103 o metod\u0103 de aliniere rigid\u0103 bazat\u0103 pe SVD, al\u0103turi de o rafinare op\u021bional\u0103 de tip ICP, pentru a raporta pozi\u021bia la modelele STL generate preoperator din scan\u0103rile CBCT. O interfa\u021b\u0103 Unity centralizeaz\u0103 vizualizarea, \u00een timp ce un server trimite corec\u021biile de naviga\u021bie c\u0103tre un robot Kuka Sunrise.<\/li>\n\n\n\n<li><strong>Segmentare la nivel de dinte (obiectiv 2):<\/strong> Pentru a ob\u021bine o geometrie stabil\u0103 a din\u021bilor \u00een prezen\u021ba ocluziilor \u0219i reflexiilor, a fost implementat modelul single-stage <strong>YOLOv8-seg<\/strong>. Antrenamentul a fost efectuat pe 420 de imagini RGB cu adnot\u0103ri manuale prin poligoane.<\/li>\n\n\n\n<li><strong>Performan\u021b\u0103 segmentare:<\/strong> Sistemul a ob\u021binut un IoU de aproximativ 0.88 \u0219i un indice DSC de aproximativ 0.92. Evaluarea de nivel instan\u021b\u0103 (Mask mAP@0.5) a fost de 0.907.<\/li>\n\n\n\n<li><strong>Avantaj arhitectural:<\/strong> Fluxul single-stage YOLO-seg genereaz\u0103 m\u0103\u0219ti mult mai stabile \u0219i o laten\u021b\u0103 considerabil redus\u0103 comparativ cu sistemul de tip YOLO+SAM, f\u0103c\u00e2ndu-l ideal pentru utilizarea \u00een timp real.<\/li>\n<\/ul>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"431\" src=\"https:\/\/hria.utcluj.ro\/wp-content\/uploads\/2026\/05\/dentistry-architecture-1024x431.png\" alt=\"\" class=\"wp-image-1831\" srcset=\"https:\/\/hria.utcluj.ro\/wp-content\/uploads\/2026\/05\/dentistry-architecture-1024x431.png 1024w, https:\/\/hria.utcluj.ro\/wp-content\/uploads\/2026\/05\/dentistry-architecture-300x126.png 300w, https:\/\/hria.utcluj.ro\/wp-content\/uploads\/2026\/05\/dentistry-architecture-768x324.png 768w, https:\/\/hria.utcluj.ro\/wp-content\/uploads\/2026\/05\/dentistry-architecture-18x8.png 18w, https:\/\/hria.utcluj.ro\/wp-content\/uploads\/2026\/05\/dentistry-architecture.png 1251w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><figcaption class=\"wp-element-caption\">Arhitectura framework-ului propus<\/figcaption><\/figure>\n<\/div>\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"691\" height=\"215\" src=\"https:\/\/hria.utcluj.ro\/wp-content\/uploads\/2026\/05\/dentistry-results.png\" alt=\"\" class=\"wp-image-1832\" srcset=\"https:\/\/hria.utcluj.ro\/wp-content\/uploads\/2026\/05\/dentistry-results.png 691w, https:\/\/hria.utcluj.ro\/wp-content\/uploads\/2026\/05\/dentistry-results-300x93.png 300w, https:\/\/hria.utcluj.ro\/wp-content\/uploads\/2026\/05\/dentistry-results-18x6.png 18w\" sizes=\"(max-width: 691px) 100vw, 691px\" \/><figcaption class=\"wp-element-caption\">Rezultate: single-stage <strong>YOLOv8-seg<\/strong> vs. YOLO+SAM (pentru compara\u021bie)<\/figcaption><\/figure>\n<\/div>","protected":false},"excerpt":{"rendered":"<p>Cercet\u0103rile vizeaz\u0103 g\u0103sirea de solu\u021bii inovatoare pentru chirurgia minim invaziv\u0103 \u0219i implantologia robotizat\u0103, elimin\u00e2nd necesitatea senzorilor hardware complec\u0219i prin utilizarea tehnicilor avansate de Computer Vision. Localizarea \u0219i pozi\u021bionarea automat\u0103 a robotului ATHENA Estimarea for\u021bei \u201esensorless\u201d \u00een chirurgia minim invaziv\u0103 Percep\u021bie \u201emarkerless\u201d pentru naviga\u021bia \u00een implantologia dentar\u0103<\/p>","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"neve_meta_sidebar":"","neve_meta_container":"default","neve_meta_enable_content_width":"on","neve_meta_content_width":100,"neve_meta_title_alignment":"","neve_meta_author_avatar":"off","neve_post_elements_order":"[\"content\"]","neve_meta_disable_header":"off","neve_meta_disable_footer":"","neve_meta_disable_title":"","_themeisle_gutenberg_block_has_review":false,"footnotes":""},"categories":[7],"tags":[],"class_list":["post-1822","post","type-post","status-publish","format-standard","hentry","category-rezultate"],"_links":{"self":[{"href":"https:\/\/hria.utcluj.ro\/en\/wp-json\/wp\/v2\/posts\/1822","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/hria.utcluj.ro\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/hria.utcluj.ro\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/hria.utcluj.ro\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/hria.utcluj.ro\/en\/wp-json\/wp\/v2\/comments?post=1822"}],"version-history":[{"count":3,"href":"https:\/\/hria.utcluj.ro\/en\/wp-json\/wp\/v2\/posts\/1822\/revisions"}],"predecessor-version":[{"id":1834,"href":"https:\/\/hria.utcluj.ro\/en\/wp-json\/wp\/v2\/posts\/1822\/revisions\/1834"}],"wp:attachment":[{"href":"https:\/\/hria.utcluj.ro\/en\/wp-json\/wp\/v2\/media?parent=1822"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hria.utcluj.ro\/en\/wp-json\/wp\/v2\/categories?post=1822"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hria.utcluj.ro\/en\/wp-json\/wp\/v2\/tags?post=1822"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}