Papers
1
Total Citations
7
H-Index
1
About
Te Xu is a researcher in robotics and computer vision, with a focus on autonomous manipulation and perception systems. Their work centers on developing intelligent methods for robot arm control, particularly in grasping tasks that require precise target recognition. In their highly cited 2020 paper, "Target Position and Posture Recognition Based on RGB-D Images for Autonomous Grasping Robot Arm Manipulation," Xu proposed a novel approach that fuses RGB and depth data to accurately detect an object's position and orientation, enabling more reliable and autonomous robotic grasping. This contribution, which has garnered 7 citations, addresses a critical challenge in industrial and service robotics: enabling machines to interact with unstructured environments. Xu's research has practical implications for manufacturing, logistics, and assistive technologies, where robots must adapt to varying objects and conditions. By advancing sensor fusion and recognition algorithms, Te Xu is helping to bridge the gap between raw visual data and actionable robotic commands, making autonomous systems more capable and efficient. Their work continues to influence developments in intelligent robotics and computer vision.
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Top Papers
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