Christian Höfert

Papers

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About

Christian Höfert is a robotics researcher whose work focuses on the intersection of 3D reconstruction, Simultaneous Localization and Mapping (SLAM), and collaborative robot manipulation. His key contributions lie in developing methodologies to evaluate the accuracy of 3D object reconstructions generated by monocular LSD-SLAM systems when deployed on collaborative robots. Höfert’s research addresses a critical gap: while SLAM is widely used for robot navigation, its feasibility for precise motion planning tasks—such as bin-picking—remains underexplored. He has demonstrated that accurate 3D reconstruction is essential for computing optimal gripper poses and enabling reliable grasping in industrial settings. His most-cited work, "Methodology to Analyze the Accuracy of 3D Objects Reconstructed with Collaborative Robot Based Monocular LSD-SLAM" (2018), has garnered 2 citations and lays the groundwork for integrating SLAM-based perception into practical robotic manipulation. By bridging the gap between navigation and manipulation, Höfert’s research advances the capabilities of collaborative robots in unstructured environments, making him a notable contributor to the fields of robotic perception and autonomous grasping.