Papers
12
Total Citations
205
H-Index
6
About
Jianjun Yi is a robotics and autonomous systems researcher whose work spans indoor positioning, mobile robot navigation, and robotic perception. His most significant contribution lies in advancing UWB-based indoor localization, with his 2020 paper on adapted error map-based mobile robot positioning accumulating over 110 citations — a testament to its practical impact on improving positioning accuracy in complex indoor environments. Yi has also made meaningful strides in addressing the longstanding challenge of global localization in repetitive environments, developing infrastructure-free hierarchical approaches that enable robots to navigate ambiguous spaces with greater reliability. His research portfolio reflects a broad systems-level perspective on autonomy: from multi-robot collision avoidance using velocity obstacle methods, to UAV-UGV cooperative landing for search and rescue missions, to autonomous navigation in unstructured outdoor terrain. More recently, Yi has pushed into robotic manipulation and perception, contributing work on workpiece pose estimation, RGB-D based arm guidance, and the novel EAGA-Net grasping detection framework. His latest Super-LIO system addresses LiDAR-inertial odometry on resource-constrained platforms, underscoring his commitment to deployable, real-world robotics solutions. Yi's cumulative body of work positions him as a versatile contributor to the field of intelligent autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1Adapted Error Map Based Mobile Robot UWB Indoor Positioning110 citations · 2020
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- 7A Study of Autonomous Landing of UAV for Mobile Platform4 citations · 2021
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