Max Robotics — Global Service Robot Directory + US Certification

About

Thomas Gulde’s research lies at the intersection of computer vision, robotics, and human-robot interaction, with a focus on enabling autonomous systems to perceive and adapt to dynamic, unstructured environments. His most influential contribution is the development of **RoPose**, a CNN-based framework for 2D pose estimation of industrial robots, which addresses the critical challenge of monitoring manipulators in mobile and collaborative workspaces. This work, along with its extension **RoPose-Real**—a real-world dataset for data-driven pose estimation—has laid the foundation for robust, vision-based robot awareness in flexible manufacturing settings. Gulde has also advanced egocentric visual hand pose estimation for robot-controlled exoskeletons, bridging human intent with robotic assistance, and explored vision-based SLAM navigation for vibro-tactile indoor guidance systems. With over 30 citations across his most-cited papers, his work is recognized for its practical impact on safe human-robot collaboration and autonomous navigation. Gulde’s contributions are particularly notable for their emphasis on real-world deployment, from dataset acquisition to system integration, making him a key figure in the push toward smarter, more responsive industrial robotics.