Max Robotics — Global Service Robot Directory + US Certification

About

Novak Zagradjanin is a researcher at the forefront of autonomous multi-robot systems, specializing in cloud-based path planning, multi-criteria decision-making, and adaptive navigation in complex, dynamic environments. His major contributions lie in developing scalable frameworks that offload computationally intensive tasks—such as real-time path optimization and online learning—to the cloud, enabling fleets of robots to operate efficiently in crowded settings like modern megastores. His most cited work, "Cloud-Based Multi-Robot Path Planning in Complex and Crowded Environment with Multi-Criteria Decision Making Using Full Consistency Method" (2019, 47 citations), introduces a novel approach that integrates fuzzy logic and decision-making algorithms to balance competing objectives like safety, efficiency, and task completion. Expanding on this, his 2021 paper (18 citations) incorporates online learning for adaptive behavior, while his exploration strategy research using the D* Lite algorithm (9 citations) addresses autonomous navigation in unknown terrains. Collectively, his works have garnered over 70 citations, reflecting their impact on advancing practical, cloud-integrated robotics for logistics and exploration. Zagradjanin’s achievements underscore a commitment to bridging theoretical decision-making with real-world robotic autonomy.