Papers
2
Total Citations
57
H-Index
2
About
Xiaolong Tang is a leading researcher in agricultural robotics and autonomous systems, with a primary focus on developing intelligent solutions for precision agriculture and robotic perception. His most impactful contribution is the design of an autonomous fruit and vegetable harvester featuring a low-cost gripper integrated with a 3D sensor, a work that has garnered 54 citations. This system employs a geometric approach to reliably detect and harvest crops with peduncles in unstructured environments, addressing a critical bottleneck in agricultural automation. Tang has also advanced mobile robot localization, proposing an improved Adaptive Monte Carlo Localization (AMCL) algorithm that integrates a virtual motion model with Normal Distributions Transform (NDT) and Extended Kalman Filter (EKF) to reduce odometry dependency. His research bridges the gap between low-cost hardware and robust autonomy, making robotic harvesting more accessible and reliable. Through these contributions, Tang is shaping the future of sustainable agriculture, enabling robots to operate effectively in complex, real-world field conditions.
Research Focus
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Top Papers
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