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About

Patrik Schmuck is a robotics researcher whose work centers on collaborative simultaneous localization and mapping (SLAM), multi-agent perception, and autonomous robotic systems. His most significant contributions lie in developing scalable, efficient frameworks that enable teams of robots to jointly map and navigate unknown environments without relying on external infrastructure such as GPS. Schmuck's landmark paper, "CCM-SLAM" (2018, 239 citations), introduced a robust centralized collaborative monocular SLAM system for robotic teams, demonstrating strong real-world applicability in domains like search-and-rescue and precision agriculture. Building on this, his 2017 work on multi-UAV collaborative monocular SLAM (182 citations) extended these capabilities to aerial platforms, and "CVI-SLAM" (2018, 128 citations) further advanced the field by integrating visual-inertial sensing for improved robustness in challenging conditions. More recently, his "COVINS" framework continued this trajectory by enabling centralized collaborative visual-inertial SLAM for multi-user and multi-robot applications. Beyond SLAM, Schmuck has contributed to distributed formation estimation for robotic swarms and large-scale 3D occupancy mapping. With cumulative citations exceeding 600, his research has meaningfully shaped how autonomous robotic teams perceive, share, and act upon environmental information — making him a notable voice in the multi-agent robotics community.