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About

Muhannad Mujahed is a leading researcher in autonomous mobile robotics, specializing in reactive collision avoidance and gap-based navigation for highly cluttered and unknown environments. His work has fundamentally advanced how robots perceive and traverse dense spaces, introducing a family of innovative gap-detection methods that prioritize safety, smoothness, and real-time performance. Among his most influential contributions is the "Admissible Gap" (AG) concept, which ensures a robot can pass through an opening while respecting its own shape and motion constraints—a breakthrough detailed in his 2017 paper (13 citations) and the widely cited 2018 work on "Admissible Gap Navigation" (31 citations). Earlier foundational papers, such as "Tangential Closest Gap (TCG) Navigation" (2013, 19 citations) and "Safe Gap based (SG) Reactive Navigation" (2013, 18 citations), established his reputation for integrating the Closest Gap strategy with tangential escape behaviors to generate safer, smoother trajectories. His "Tangential Gap Flow (TGF)" method (2016, 29 citations) further extended reactive navigation into extremely dense environments. With over 120 total citations, Mujahed’s research provides essential frameworks for autonomous systems operating in real-world, unpredictable settings, making his work indispensable for students and engineers developing robust mobile robots.