Xiaoxi Jiang
Papers
1
Total Citations
28
H-Index
1
About
Xiaoxi Jiang is a leading researcher in humanoid robotics, with a primary focus on motion planning and control in dynamic environments. Their most cited work, "Learning humanoid reaching tasks in dynamic environments" (2007, 28 citations), tackles a central challenge in the field: enabling humanoid robots to plan and execute complex tasks when surroundings are constantly changing. Jiang demonstrated that while sampling-based online motion planners are effective for known, dynamic settings, they lack adaptability without learning strategies. This insight paved the way for integrating machine learning into real-time robotic control, allowing robots to generalize from past experiences rather than recomputing solutions from scratch. By bridging the gap between traditional planning algorithms and adaptive learning, Jiang’s contributions have influenced subsequent work in autonomous manipulation and human-robot interaction. Their research remains a foundational reference for engineers seeking to build robots that can operate safely and efficiently in unstructured, real-world environments.
Research Focus
Key Achievements
Top Papers
- 1Learning humanoid reaching tasks in dynamic environments28 citations · 2007