Max Robotics — Global Service Robot Directory + US Certification

About

Jihong Zhu’s research lies at the intersection of robotic manipulation, perception, and control, with a particular focus on enabling robots to operate safely and intelligently in unstructured, real-world environments. His work spans three core areas: 3D perception for autonomous systems, the manipulation of complex objects (including deformable and composite rigid-deformable objects), and robust adaptive control for nonlinear systems. A key contribution is his development of methods for robotic manipulation of composite rigid-deformable objects, where he introduced contour-moment-based shape/position control with finite-time model estimation—a challenging problem with clear practical applications in agriculture and service robotics. His highly cited paper “The Art of Defense” (2023, 19 citations) addresses adversarial robustness in 3D point-cloud perception, critical for autonomous cars and robots. Other influential works include LiDAR-based field-ground segmentation for agricultural robots (FGSeg, 18 citations) and appearance-based visual servoing using wavelet neural networks (18 citations). With over 80 total citations across his top papers, Zhu’s contributions are advancing the frontier of robot autonomy, from adaptive neural control to task-parameterized skill learning from few demonstrations. His recent work on dual-arm collaborative manipulation and semantic segmentation for agroforestry environments further underscores his commitment to deploying robots in complex, natural settings.