Jiu-Lou Yan

About

Jiu-Lou Yan is a pioneering roboticist whose research centers on the design, control, and networking of inspection and humanoid robots. His most impactful contribution is the development of the NTU Navigator, a lightweight, modular pipe inspection robot introduced in 2009. This work, which has garnered 62 citations, revolutionized in-pipe inspection by enabling easy manipulation and repair through a modular design and fuzzy logic control. Yan further advanced the field with an earlier GUI-controlled version of the robot in 2007. In humanoid robotics, he has made significant strides in real-time networking, proposing the RTNET communication approach for humanoid robots in 2017. His work on walking pattern generation is equally notable, including a state-incremental optimal control method for 3D COG patterns and a fast, smooth walking generator using Jacobian inverse kinematics. Yan has also developed footstep-planning algorithms for 3D environments and real-time walking stabilizers that do not require prior knowledge of floor conditions. With a career spanning over a decade, his contributions to robot locomotion and inspection systems continue to influence both industrial applications and academic research in robotics.

Research Focus

Key Achievements

Top Papers

1. 1
   Development and Fuzzy Control of a Pipe Inspection Robot

   62 citations · 2009
2. 2
   Development of a Pipe Inspection Robot

   18 citations · 2007
3. 3
   IoT-based networking for humanoid robots

   10 citations · 2017
4. 4
   State-incremental optimal control of 3D COG pattern generation for humanoid robots

   10 citations · 2013
5. 5
   A fast and smooth walking pattern generator of biped robot using Jacobian inverse kinematics

   8 citations · 2007
6. 6
   Footprint searching and trajectory design of a humanoid robot

   2 citations · 2012
7. 7
   Development of a walking stabilizing controller for humanoid robots

   2 citations · 2010

Key Collaborators

Contact & Links