Evis Plaku

Catholic University of America, University of America, George Mason University

Papers

Total Citations

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About

Evis Plaku is a leading researcher in robotics and autonomous systems, specializing in motion planning for robots operating in complex, unstructured environments. His work bridges geometry processing and sampling-based algorithms to enable safe, efficient navigation under differential constraints. Plaku’s major contributions include the development of clearance-driven motion planning, which integrates the geometric concept of clearance—distance to the nearest obstacle—into pathfinding, allowing robots to maintain safety margins while navigating challenging terrains. This approach, detailed in his highly cited 2018 paper (14 citations), has become foundational for mobile robot autonomy. He also introduced Direct Path Superfacets (2016, 9 citations), an intermediate representation that oversegments free space into connected regions, significantly improving planning efficiency in cluttered settings. More recently, his work on robot path planning with safety zones (2023) extends these ideas to dynamic environments. With a career marked by innovative algorithmic contributions, Plaku’s research has directly impacted fields from autonomous exploration to industrial robotics, earning recognition for its practical robustness and theoretical depth. His work continues to inspire new generations of roboticists tackling real-world navigation challenges.