Max Robotics — Global Service Robot Directory + US Certification

About

Jan Steinbrener is a leading researcher at the intersection of robotics, computer vision, and AI, with a primary focus on enabling autonomous systems to perceive and interact with their environments with exceptional precision. His work centers on 6-DoF pose estimation, visual-inertial odometry, and robot-assisted medical imaging, consistently pushing the boundaries of what is possible in real-world, unstructured settings. Steinbrener’s most impactful contribution is the **PoET (Pose Estimation Transformer)** framework, a novel approach for single-view, multi-object 6D pose estimation that has garnered 28 citations since 2022, addressing a critical challenge for robotic grasping and localization. He also led the development of the **INSANE dataset** (11+ citations), a rich, multi-sensor resource designed to advance UAV navigation in challenging environments, including Mars-analog terrain. In the medical domain, his work on a **twin robotic X-ray system** (24 citations) and AI-driven needle detection for robot-assisted ultrasound interventions (12 citations) demonstrates a commitment to translating cutting-edge robotics into life-saving clinical tools. Steinbrener’s research is characterized by a pragmatic approach to bridging the simulation-to-real gap, as seen in his reinforcement learning framework for cable-driven parallel robots (CaRoSaC), and his contributions to collaborative state estimation under communication constraints. With over 100 total citations, he is a rising star whose work is shaping the future of autonomous navigation, robotic perception, and intelligent medical systems.