Max Robotics — Global Service Robot Directory + US Certification

About

Stephan Weiss is a leading researcher in robotic perception and state estimation, with a focus on enabling autonomous systems to operate reliably in complex, real-world environments. His core contributions span 6D object pose estimation, multi-robot collaborative localization, and sensor fusion for unmanned aerial vehicles (UAVs). Weiss introduced **PoET (Pose Estimation Transformer)**, a novel transformer-based architecture for single-view, multi-object 6D pose estimation that addresses challenges like occlusion and object symmetries—critical for robotic grasping and manipulation. He also developed **centralized-equivalent pairwise estimation** methods that achieve statistically optimal multi-robot state estimation under asynchronous communication constraints, overcoming computational and overhead limitations of prior work. To accelerate research in robust localization, Weiss created the **INSANE dataset**, a cross-domain, multi-sensor UAV dataset designed to benchmark advanced estimators across diverse environments. His work on **AI-based multi-object relative state estimation with self-calibration** further pushes the boundaries of autonomous infrastructure inspection by enabling UAVs to extract semantic information from raw sensory data without external calibration. With over 40 citations across his most impactful papers, Weiss’s research is foundational for next-generation autonomous robotics, bridging perception, estimation, and real-world deployment.