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About

Roi Yehoshua is a robotics researcher whose work has made significant contributions to the field of robotic coverage planning, with a particular focus on adversarial environments. His research addresses a compelling and practical challenge: how can robots efficiently cover an area when threats exist that may disable them mid-mission? Yehoshua formally introduced and developed the concept of *adversarial coverage*, a richer and more realistic extension of classical coverage path planning that balances speed with survivability. Across a series of influential publications spanning 2013 to 2016, Yehoshua systematically built out this research agenda — from formally defining the problem and establishing optimization criteria, to developing algorithms for safest-path navigation, online planning, adversarial threat modeling, and multi-robot coordination. His 2016 paper on robotic adversarial coverage in known environments stands as his most cited work, accumulating 38 citations and serving as a cornerstone reference in the area. In total, his body of work has garnered nearly 100 citations, reflecting strong uptake within the robotics and AI planning communities. Students interested in mobile robotics, path planning under uncertainty, or human-robot interaction in dangerous environments will find Yehoshua's work both foundational and highly applicable to real-world scenarios such as search-and-rescue and hazardous environment inspection.