Muhammad Imran

Papers

Total Citations

H-Index

About

Muhammad Imran’s research focuses on advancing autonomous navigation and path planning for mobile robots, with a particular emphasis on optimizing both efficiency and safety. His most cited work, “A hybrid path planning technique developed by integrating global and local path planner” (2016), addresses a core challenge in robotics: finding not just any path, but a high-quality, optimal trajectory. By fusing global and local planning strategies, Imran’s approach improves the distance a robot travels from start to goal while ensuring its safety in dynamic environments. This contribution has garnered 18 citations, reflecting its relevance to researchers tackling real-world robotic navigation. Imran’s work is notable for bridging theoretical planning algorithms with practical implementation, offering a balanced solution between path length and collision avoidance. His research is particularly valuable for students and engineers working on autonomous systems, as it demonstrates how hybrid methods can overcome the limitations of standalone planners. Through this work, Imran has helped shape more reliable and efficient robotic movement, contributing to the broader goal of creating truly autonomous machines capable of navigating complex, unpredictable spaces.