Max Robotics — Global Service Robot Directory + US Certification

About

Simon Boche is a robotics researcher specializing in simultaneous localization and mapping (SLAM), state estimation, and autonomous navigation for mobile robots. His work focuses on the tight integration of multiple sensor modalities — including visual, inertial, LiDAR, and GPS systems — to push the boundaries of robustness and accuracy in real-world robotic deployments. Boche's most influential contribution, "Visual-Inertial SLAM with Tightly-Coupled Dropout-Tolerant GPS Fusion" (2022, 20 citations), demonstrated how GPS can be seamlessly fused with visual-inertial systems even under signal dropout conditions, a critical challenge for outdoor autonomy. Building on this foundation, he developed tightly-coupled LiDAR-Visual-Inertial SLAM with large-scale volumetric occupancy mapping (2024, 13 citations), enabling globally consistent 3D environment representation essential for real-world robot deployment. His OKVIS2-X system (2025) represents a culmination of this work, offering a configurable, multi-sensor SLAM framework capable of dense mapping at scale. More recently, Boche has explored uncertainty-aware mapping using deep neural network depth predictions and autonomous MAV exploration, reflecting a growing interest in intelligent, self-directed robotic systems. His research collectively addresses the full autonomy pipeline, making him an emerging voice in the mobile robotics and SLAM community.