Shujun Lu

About

Shujun Lu is a leading figure in human-robot collaboration, with a career dedicated to making industrial robots safer and more intuitive in shared workspaces. His research centers on collision detection, human-robot interaction, and intelligent path planning. Lu’s most influential contribution is a pioneering method for collision detection and identification using wrist and base force/torque sensors, detailed in his 2006 paper (69 citations). This work, which employs an impact model alongside neural network and model-based approaches, allows a manipulator to sense and respond to unexpected contact with humans or the environment—a critical step toward truly safe coexistence. He further refined this concept in a related 2006 study (10 citations), and extended his vision to proactive safety with a 2005 paper on weighted path planning (3 citations), which enables robots to navigate around humans without hardware modifications. By integrating sensor-driven awareness into standard industrial controllers, Lu’s work has laid essential groundwork for the next generation of collaborative robots, directly influencing how researchers and engineers design safer, more adaptive human-robot workspaces.

Research Focus

Key Achievements

Top Papers

1. 1
   Human-Robot Collision Detection and Identification Based on Wrist and Base Force/Torque Sensors

   69 citations · 2006
2. 2
   Human-robot interaction detection: a wrist and base force/torque sensors approach

   10 citations · 2006
3. 3
   Weighted path planning based on collision detection

   3 citations · 2005

Key Collaborators

Contact & Links