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About

Dena Kadhim Muhsen is a rising researcher in the field of robotics, with a focused expertise in swarm intelligence and autonomous path planning. Her work addresses critical challenges in robotic navigation and area coverage, particularly through the enhancement of the Rapidly Exploring Random Tree (RRT) algorithm. Muhsen’s major contributions include the development of novel hybrid algorithms that integrate metaheuristic optimization with traditional path planning. Notably, she proposed the Improved RRT using the Salp Swarm Algorithm (IRRT-SSA) and the Memorized RRT Optimization (MRRTO), both designed to overcome the RRT’s limitation of not guaranteeing optimal paths. Her comprehensive survey on swarm robotics for area coverage problems has garnered significant attention, alongside a systematic review of RRT algorithms for single and multiple robots, each accumulating 9 citations. These works are foundational for applications in exploration, surveillance, and autonomous navigation. Muhsen’s innovative approach to algorithm enhancement positions her as a promising contributor to the next generation of efficient, multi-robot systems. Her research is particularly valuable for students and engineers seeking to understand and improve autonomous robotic coordination in complex environments.