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About

Amin Hammad is a leading researcher at the intersection of construction robotics, automation, and Building Information Modeling (BIM). His work focuses on enhancing the safety and productivity of earthwork operations, particularly through the development of intelligent path planning for heavy machinery like excavators. Hammad’s major contributions include pioneering the use of heuristic rules to improve the performance of Rapidly-exploring Random Tree (RRT) algorithms for excavator navigation, a critical advancement for congested construction sites where collision risks are high. He has also been instrumental in developing ontologies for BIM-based robotic navigation and inspection tasks, enabling more efficient and autonomous building inspections. With papers like "Improving the performance of RRT path planning of excavators by embedding heuristic rules" (13 citations) and "Ontology for BIM-Based Robotic Navigation and Inspection Tasks" (8 citations), his work has garnered attention for its practical applications. Notably, Hammad’s early work on a flexible automated foam cutting system (1997) demonstrates his long-standing commitment to automation in construction. His research directly addresses real-world challenges, making him a key figure in advancing smart construction technologies.