Papers
7
Total Citations
108
H-Index
4
About
Hangen He is a robotics researcher whose work spans path planning, vision-based perception, and intelligent control for autonomous systems. He is best known for developing "Triple RRTs," an innovative path-planning method that addresses the long-standing challenge of navigating narrow passages in high-dimensional configuration spaces—a critical problem for robots with many degrees of freedom. His 2010 paper on this method has accumulated 31 citations and remains a reference in sampling-based planning. He has also made significant contributions to vision-based object detection for robotic applications, with his 2017 deep learning approach cited 33 times, and to field robot navigation through a hierarchical vision sensor method for robust road detection under challenging conditions. Beyond perception and planning, He has explored reinforcement learning for optimal control of under-actuated robots, such as the acrobot, and kernel-based approximate dynamic programming for autonomous vehicle path tracking. His work on ultrasonic ranging using spread spectrum modulation and immune-inspired mobile robot programming further demonstrates his breadth in sensor integration and bio-inspired control. With over 100 total citations, He’s research provides practical solutions for real-world robotic autonomy, from industrial manipulators to field robots.
Research Focus
Key Achievements
Top Papers
- 1
- 2Triple RRTs: An Effective Method for Path Planning in Narrow Passages31 citations · 2010
- 3Vision Sensor-Based Road Detection for Field Robot Navigation24 citations · 2015
- 4
- 5Novel Ultrasonic Ranging Approach Based on Spread Spectrum Modulation4 citations · 2006
- 6
- 7Immune modelling and programming of a mobile robot demo4 citations · 2006