Junbo Xin

Shenzhen Institute of Information Technology

Papers

Total Citations

H-Index

About

Junbo Xin is a robotics researcher specializing in autonomous navigation, intelligent control, and human-robot interaction for mobile platforms. His work focuses on enabling robots to operate effectively in complex, real-world indoor environments. A key contribution is his method for detecting, locating, and crossing narrow doorways using a Kinect sensor, which allows large surveillance robots to autonomously patrol entire building interiors—a critical capability for practical deployment. This foundational work has garnered 17 citations. Xin also advanced learning-based control for dynamically unstable systems, developing a support vector regression method to balance a two-wheeled self-balancing robot. This approach demonstrated how machine learning can replace traditional PID controllers for complex stabilization tasks, earning 6 citations. His research bridges the gap between perception and action, tackling the practical challenges of making robots both mobile and stable. By combining computer vision for environmental understanding with adaptive control algorithms, Xin has contributed to the development of more capable and autonomous service robots for security and domestic applications.