Ryan Meuth

Missouri University of Science and Technology

Papers

Total Citations

H-Index

About

Ryan Meuth’s research centers on robotic area coverage, multi-vehicle coordination, and accessible robotics platforms. His most influential work, “Adaptive task allocation for search area coverage” (23 citations), addresses critical challenges in autonomous search-and-rescue, surveillance, and agricultural spraying by developing algorithms that adapt to varying vehicle and environmental conditions. Meuth further advanced path planning with his “Divide and conquer evolutionary TSP solution for vehicle path planning” (12 citations), which efficiently solves the traveling salesman problem for robotic coverage tasks like cleaning and machine tooling. Beyond theoretical contributions, Meuth created the LabRat™ miniature robot kit (9 citations), an autonomous mobile platform designed for students, researchers, and hobbyists. This self-contained robot features batteries, motors, whisker sensors, and infrared proximity sensors for “Rat-to-Rat” communication, democratizing robotics education and experimentation. Meuth’s work bridges algorithmic innovation with practical, accessible hardware, making him a notable figure in adaptive robotics and educational tool development.