Max Robotics — Global Service Robot Directory + US Certification

About

Tiberiu Cocias is a robotics researcher whose work focuses on the intersection of computer vision and service robotics, particularly in enabling robots to perceive and interact with their environments. His key research areas include 3D scene reconstruction, camera pose estimation, and object segmentation for robotic manipulation. Cocias made significant contributions to robust camera pose and scene structure analysis, as demonstrated in his most-cited paper (23 citations), which addresses the challenge of determining a robot's position relative to its surroundings. He also developed innovative methods for object surface estimation using multiple-superquadrics (12 citations), allowing robots to approximate object volumes for effective grasp planning. His work on Generic Fitted Shapes (GFS) advanced volumetric object segmentation in service robotics contexts. Cocias further explored real-time machine vision systems for robotic scene perception, integrating stereo vision to simultaneously estimate 3D camera pose and object structure. His research has practical implications for autonomous service robots operating in unstructured environments, bridging the gap between raw sensor data and actionable spatial understanding.