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About

Tianjian Lei is a robotics researcher whose work centers on intelligent robotic manipulation, particularly in the domains of automated grinding, contact dynamics, and high-fidelity simulation. His research addresses critical challenges in industrial automation, focusing on how robots can perceive, plan, and execute complex physical tasks with precision. Lei’s most cited work, “Automatic Aluminum Alloy Surface Grinding Trajectory Planning of Industrial Robot Based on Weld Seam Recognition and Positioning” (2023, 17 citations), introduces a novel method for planning grinding trajectories on curved surfaces, integrating weld seam recognition and defect positioning to significantly improve the efficiency of large-scale aluminum alloy surface finishing. He further advances the field with his development of a “Variable Time-Step Physics Engine with Continuous Compliance Contact Model for Optimal Robotic Grinding Trajectory Planning” (2024), which tackles the persistent problem of inaccurate simulation-to-reality transfer. Complementing this, his work on a “Robotic Simulator with High-Precision Perception of Contact Dynamics” (2023) establishes a foundational tool for comprehensive robot training by employing a continuous compliant contact model. Together, Lei’s contributions are shaping the next generation of intelligent, simulation-driven robotic systems for manufacturing.