Max Robotics — Global Service Robot Directory + US Certification

About

Tianhao Wu is a robotics researcher whose work bridges perception, manipulation, and autonomous navigation in complex, real-world environments. His key research areas include simultaneous localization and mapping (SLAM), robot learning, and precision agriculture robotics. Wu’s major contributions are threefold: he co-developed the SubT-MRS dataset (46 citations), which pushes SLAM toward all-weather, resilient performance by addressing a critical gap in existing datasets; he contributed to PyPose (35 citations), a library that fuses deep learning with physics-based optimization for more generalizable robot learning; and he designed a mobile robotics platform for strawberry sensing and harvesting (34 citations), advancing indoor precision farming. His work on dynamic grasping via adversarial reinforcement learning (GraspARL) and multi-robot furniture assembly (RoboAssembly) further showcases his versatility in tackling contact-rich manipulation tasks. With over 120 total citations and publications spanning 2021–2024, Wu is establishing himself as a rising figure in embodied AI and field robotics, where his contributions are directly shaping the next generation of robots that can see, move, and interact robustly in unstructured environments.