Papers
4
Total Citations
17
H-Index
3
About
Wenjiang Li is a robotics researcher whose work spans the critical intersection of perception, control, and human-robot interaction. His primary research areas include 6D object pose estimation for robotic grasping, autonomous navigation using ROS, and adaptive control for rehabilitation exoskeletons. Li's most impactful contribution is his work on "Estimating 6D Object Poses with Temporal Motion Reasoning for Robot Grasping in Cluttered Scenes" (2022, 8 citations), which addresses the challenging problem of occluded object pose estimation in human-robot collaboration scenarios—a key bottleneck for vision-based manipulation. He has also advanced practical inspection robotics by developing a ROS-based control system for electric power inspection robots (2021, 4 citations), reducing development costs and maintenance complexity. In rehabilitation robotics, Li proposed a force estimation-based adaptive impedance control strategy for lower-limb exoskeletons (2023, 3 citations), enabling effective physical human-robot interaction without dedicated force sensors. His early work on AIMLBot intelligent robots for virtual reference services (2012) demonstrates his long-standing interest in autonomous systems. With a growing citation record and contributions spanning perception, control, and practical deployment, Li is establishing himself as a versatile researcher advancing both the theoretical foundations and real-world applications of intelligent robotic systems.
Research Focus
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Top Papers
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