Max Robotics — Global Service Robot Directory + US Certification

About

Joko Hariyono’s research lies at the intersection of autonomous navigation, computer vision, and mobile robotics, with a focus on enabling intelligent vehicles and robots to perceive and move through their environments. His major contributions include developing a global path planning method for unmanned ground vehicles using road map images, which constructs the shortest path for automatic navigation—a foundational task for autonomous driving systems. He has also advanced human and moving object detection from mobile omnidirectional cameras, notably through ego-motion compensation techniques that allow robots to distinguish moving objects from camera-induced motion. In the domain of 3D reconstruction, Hariyono proposed a geometry-based method to recover real-size 3D scenes from a single omnidirectional image, moving beyond scale-only models to support practical applications. His work has garnered citations across these areas, with his 2014 path planning paper receiving 20 citations, reflecting its relevance to autonomous vehicle research. Hariyono’s contributions are particularly notable for addressing real-world challenges in mobile robot perception and navigation, making his research valuable for students and engineers working on autonomous systems, robotics, and computer vision.