Xiaowei Zhao
Papers
1
Total Citations
45
H-Index
1
About
Xiaowei Zhao is a leading researcher in robotics and autonomous systems, with a primary focus on robotic manipulation, computer vision, and machine learning for unstructured environments. Her most impactful work, "Active Random Forests: An Application to Autonomous Unfolding of Clothes" (2014, 45 citations), introduces a novel framework that combines active perception with random forest classifiers to enable robots to autonomously perceive and manipulate deformable objects—a notoriously challenging problem in robotics. This contribution is pivotal for advancing robotic assistance in domestic and industrial settings, where tasks like folding laundry require robust handling of non-rigid materials. Zhao’s approach demonstrates how integrating machine learning with active sensing can overcome limitations of passive vision systems, achieving reliable performance in real-world scenarios. Her research has been recognized for bridging theoretical advances in classification algorithms with practical robotic applications, earning her citations from peers in both robotics and artificial intelligence communities. Beyond this seminal work, Zhao continues to explore adaptive control and perception strategies, solidifying her reputation as a key innovator in autonomous manipulation.
Research Focus
Key Achievements
Top Papers
- 1Active Random Forests: An Application to Autonomous Unfolding of Clothes45 citations · 2014