We’re excited to share our latest work, “iLSPR: a learning-based scene point-cloud registration method for robotic spatial awareness in intelligent manufacturing,” by Yusen Wan and Xu Chen, now published in Robotics and Computer-Integrated Manufacturing (Vol. 99, 2026). This publication marks an important step toward enabling robots to achieve high-precision spatial awareness in real-world industrial environments—where accuracy matters most and data is often scarce.
It all began with a single glance in the crowd. My mentorship journey with Toby has been a truly unique story. When Toby first joined the group, he wasn’t someone rushing headlong into the world of robotics. He simply wanted to make his master’s experience more meaningful, to add weight to the journey. So I chose a mathematically inclined project for us to explore together-starting from fundamentals, seeking depth over speed.
From snowboarding examples to fully reworked lecture materials, it has been a blast with the students.
🌟 Every project, every journey, is a precious treasure. 💎 Every student, every class, is an invaluable gem. This year, I’ve started to carefully reflect on and organize these treasures and gems—each representing a milestone of growth and learning.
