{"id":52726,"date":"2025-12-15T08:09:25","date_gmt":"2025-12-15T13:09:25","guid":{"rendered":"https:\/\/www.uqac.ca\/uqactualites\/?p=52726"},"modified":"2025-12-15T11:28:02","modified_gmt":"2025-12-15T16:28:02","slug":"ahmad-merei-etudiant-au-doctorat-en-informatique-soutient-sa-these","status":"publish","type":"post","link":"https:\/\/www.uqac.ca\/uqactualites\/2025\/12\/15\/ahmad-merei-etudiant-au-doctorat-en-informatique-soutient-sa-these\/","title":{"rendered":"Ahmad Merei, \u00e9tudiant au doctorat en informatique, soutient sa th\u00e8se"},"content":{"rendered":"

Finissant au doctorat en informatique<\/a>, Ahmad Merei a effectu\u00e9 sa soutenance de th\u00e8se le 12 d\u00e9cembre 2025. Sous la direction de recherche d’Hamid Mcheick<\/a> et la codirection d’Alia Ghaddar (Universit\u00e9 internationale libanaise), sa th\u00e8se a pour titre \u00ab Energy-aware informative path planning and emergency safe landing approach for UAVs in search and rescue missions<\/em> \u00bb.<\/p>\n

Sous la pr\u00e9sidence de Fehmi Jaafar (UQAC), le jury d’\u00e9valuation \u00e9tait compos\u00e9 d’Enrico Natalizio (Technology Innovation Institute)\u00a0 et de Djamal Rebaine (UQAC).<\/p>\n

\n
R\u00e9sum\u00e9 de la th\u00e8se<\/h5>\n

Les v\u00e9hicules a\u00e9riens sans pilote (UAV \u2013 Uncrewed Aerial Vehicles) sont de plus en plus utilis\u00e9s dans les domaines de la sant\u00e9, de la gestion des catastrophes et des op\u00e9rations de recherche et sauvetage (SAR). Dans ces environnements, la prise de d\u00e9cision rapide est essentielle. Elle s’effectue dans des environements complexes et incertains, ou chaque instant compte et peut sauver des vies. Cependant, leur efficacit\u00e9 demeure limit\u00e9e par trois d\u00e9fis majeurs.<\/p>\n

\nVoir plus<\/strong><\/summary>\n

Le premier d\u00e9fi consiste \u00e0 explorer efficacement une zone d\u2019int\u00e9r\u00eat (AOI \u2013 {Area of Interest}). L’objectif est d’identifier et de prioriser les r\u00e9gions informatives importantes (ROI \u2013 Regions of Interest). Ces missions sont \u00e0 la fois critiques en temps, o\u00f9 chaque minute peut d\u00e9terminer les chances de survie, et critiques en \u00e9nergie, o\u00f9 la capacit\u00e9 limit\u00e9e des batteries restreint l\u2019endurance de vol. Le deuxi\u00e8me d\u00e9fi concerne la coordination de plusieurs UAVs. Il s’agit de r\u00e9partir les t\u00e2ches de mani\u00e8re \u00e9quilibr\u00e9e entre les diff\u00e9rentes ROI, tout en \u00e9vitant l\u2019exploration redondante et le gaspillage d\u2019\u00e9nergie. Enfin, le troisi\u00e8me d\u00e9fi r\u00e9side dans la garantie d\u2019atterrissages autonomes en toute s\u00e9curit\u00e9. Il s’agit, d’une part, la capacit\u00e9 \u00e0 se poser dans des zones encombr\u00e9es \u00e0 proximit\u00e9 de survivants, afin de faciliter la communication avec les premiers intervenants. D’autre part, le syst\u00e8me doit g\u00e9rer des situations impr\u00e9visibles telles que les environnements sans GPS ou des urgences n\u00e9cessitant un atterrissage imm\u00e9diat.<\/p>\n

Les approches existantes de planification de trajectoire informative, qu\u2019elles soient mono-UAV ou multi-UAV, ont permis des avanc\u00e9es notables. Cependant elles peinent encore \u00e0 surmonter certaines limites en pratiques: l\u2019utilisation optimale de l\u2019\u00e9nergie, la maximisation de la couverture de mission, ainsi que la coordination efficace de plusieurs v\u00e9hicules.
\nDe m\u00eame, les syst\u00e8mes d\u2019atterrissage existants \u00e9chouent souvent \u00e0 \u00e9viter les obstacles. Par ailleurs, l\u2019int\u00e9gration des informations relatives aux survivants dans les algorithmes de d\u00e9cision en situation d\u2019urgence reste partielle. De plus, ces syst\u00e8mes s\u2019appuient fr\u00e9quemment sur des zones d\u2019atterrissage pr\u00e9-d\u00e9finies, qui sont rarement disponibles dans les sc\u00e9narios r\u00e9els de recherche et sauvetage (SAR).<\/p>\n

Cette th\u00e8se r\u00e9pond \u00e0 ces d\u00e9fis \u00e0 travers trois contributions principales. Premi\u00e8rement, elle introduit un planificateur de trajectoire informative \u00e0 deux \u00e9tapes anticip\u00e9es et \u00e0 conscience \u00e9nerg\u00e9tique (not\u00e9 EA-IPP2n). Ce planificateur est con\u00e7u pour maximiser le gain d\u2019information tout en consid\u00e9rant explicitement le temps et l\u2019\u00e9nergie comme ressources critiques de mission. Deuxi\u00e8mement, elle \u00e9tend ce cadre aux op\u00e9rations coop\u00e9ratives. Pour cela, elle propose une strat\u00e9gie de partitionnement en forme de V (not\u00e9 VAP) et un planificateur de trajectoire informative multi-UAV \u00e0 conscience \u00e9nerg\u00e9tique (not\u00e9 EA-MIPP). Cette approche permet une r\u00e9partition \u00e9quilibr\u00e9e des t\u00e2ches entre les ROI, tout en g\u00e9rant les obstacles statiques et les zones de non-vol. Troisi\u00e8mement, elle d\u00e9veloppe un syst\u00e8me d\u2019atterrissage d\u2019urgence s\u00e9curis\u00e9 (not\u00e9 ESLS). Ce systeme int\u00e9gre plusieurs modules: la cartographie, la localisation et la d\u00e9tection d\u2019objets afin d\u2019identifier de mani\u00e8re autonome des zones d\u2019atterrissage s\u00fbres. De plus, un mode sp\u00e9cialis\u00e9 est prevu pour privil\u00e9gier les atterrissages \u00e0 proximit\u00e9 des survivants d\u00e9tect\u00e9s.<\/p>\n

Ensemble, ces contributions forment un cadre unifi\u00e9 pour l\u2019autonomie des UAVs, \u00e0 la fois conscient des ressources et r\u00e9silient dans l\u2019ex\u00e9cution des missions. Les m\u00e9thodes propos\u00e9es am\u00e9liorent la collecte d\u2019informations dans les AOI, permettent une collaboration multi-UAV et assurent des atterrissages d\u2019urgence s\u00e9curis\u00e9s. En combinant planification de trajectoire \u00e9nerg\u00e9tique et strat\u00e9gies d\u2019atterrissage adaptatives, cette recherche renforce les capacit\u00e9s op\u00e9rationnelles des UAV dans les missions de sant\u00e9 et de recherche et sauvetage.<\/p>\n<\/details>\n

\n

F\u00e9licitations \u00e0 Ahmad Merei pour la soutenance de sa th\u00e8se de doctorat!<\/p>\n","protected":false},"excerpt":{"rendered":"

Finissant au doctorat en informatique, Ahmad Merei a effectu\u00e9 sa soutenance de th\u00e8se le 12 d\u00e9cembre 2025. Sous la direction de recherche d’Hamid Mcheick et la codirection d’Alia Ghaddar (Universit\u00e9 internationale libanaise), sa th\u00e8se a pour titre \u00ab Energy-aware informative path planning and emergency safe landing approach for UAVs in search and rescue missions \u00bb. […]<\/p>\n","protected":false},"author":5,"featured_media":52729,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[2844,248],"tags":[20,3004,427,293],"yoast_head":"\r\nAhmad Merei, \u00e9tudiant au doctorat en informatique, soutient sa th\u00e8se - UQACtualit\u00e9s<\/title>\r\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\r\n<link rel=\"canonical\" href=\"https:\/\/www.uqac.ca\/uqactualites\/2025\/12\/15\/ahmad-merei-etudiant-au-doctorat-en-informatique-soutient-sa-these\/\" \/>\r\n<meta property=\"og:locale\" content=\"fr_CA\" \/>\r\n<meta property=\"og:type\" content=\"article\" \/>\r\n<meta property=\"og:title\" content=\"Ahmad Merei, \u00e9tudiant au doctorat en informatique, soutient sa th\u00e8se - UQACtualit\u00e9s\" \/>\r\n<meta property=\"og:description\" content=\"Finissant au doctorat en informatique, Ahmad Merei a effectu\u00e9 sa soutenance de th\u00e8se le 12 d\u00e9cembre 2025. 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