Theodore W. Manikas

University of Tulsa, University of Pittsburgh

Papers

Total Citations

356

H-Index

About

Theodore W. Manikas is a researcher specializing in autonomous robotics, evolutionary computation, and intelligent navigation systems. His work has made significant contributions to the field of mobile robot path planning, particularly through the innovative application of genetic algorithms to solve complex navigation challenges in dynamic environments. Manikas is perhaps best known for his 2005 paper "Autonomous Local Path Planning for a Mobile Robot Using a Genetic Algorithm," which has garnered 186 citations and remains a foundational reference for researchers developing obstacle avoidance strategies. This work demonstrated that genetic algorithms could identify not merely valid paths but genuinely optimal routes through constrained search spaces. His follow-up work in 2007, "Genetic Algorithms for Autonomous Robot Navigation" (115 citations), extended these principles into practical instrumentation and measurement contexts where human access is limited or dangerous. Beyond navigation optimization, Manikas has also contributed methodologically to the field by developing frameworks for generating and taxonomizing diverse robot path planning problems, enabling more rigorous benchmarking of navigation algorithms. His earlier 2003 research introduced a novel value-encoded genetic algorithm that improved information efficiency within the GA structure itself. Collectively, his body of work has shaped how researchers approach intelligent, autonomous navigation and continues to influence robotics and evolutionary computation communities worldwide.