Max Robotics — Global Service Robot Directory + US Certification

About

Ni Ou is an emerging researcher working at the intersection of robotic perception, sensor calibration, and tactile sensing — fields increasingly critical to the advancement of autonomous systems and intelligent robotics. Their work spans two complementary domains: multi-modal sensor fusion for autonomous vehicles and vision-based tactile sensing for robotic manipulation. In the realm of sensor calibration, Ou has made notable contributions through targetless LiDAR-camera calibration, leveraging cross-modality structural consistency to enable precise extrinsic calibration without reliance on physical targets — a significant practical advancement for real-world deployment of automated vehicles, accumulating 14 citations across related publications. Ou's tactile sensing research is particularly distinguished. Their development of a mode-switchable optical tactile sensor (9 citations) elegantly bridges marker and markerless sensing paradigms, broadening applicability across diverse robotic tasks. Further work on deep domain adaptation for force calibration (8 citations) and the innovative TransForce framework for transferable force prediction (5 citations) addresses critical bottlenecks in data acquisition and sensor generalization. Collectively, these contributions reflect Ou's commitment to building robust, adaptable sensing systems that bring robots closer to human-like dexterity and environmental awareness.