Nanjun Li
Papers
2
Total Citations
89
H-Index
2
About
Nanjun Li is a leading researcher in robotic manipulation and computer vision, with a primary focus on advancing grasp detection for autonomous systems. His most impactful work, "High-Performance Pixel-Level Grasp Detection Based on Adaptive Grasping and Grasp-Aware Network" (2021, 79 citations), revolutionized planar grasping by introducing a pixel-level detection method that adaptively predicts grasp configurations for every pixel, overcoming the limitations of discrete gripper pose estimation. This approach significantly improves accuracy in cluttered, uncertain environments by capturing a continuous distribution of feasible grasps. Building on this, Li’s 2023 study "On-Policy and Pixel-Level Grasping Across the Gap Between Simulation and Reality" (10 citations) tackles the critical sim-to-real transfer problem, proposing a method that aligns training data from synthetic 3D models with real-world image evaluations. This work bridges a persistent gap in robotic learning, enabling more reliable deployment of grasping algorithms. Li’s contributions are vital for advancing industrial automation and service robotics, where robust, pixel-level perception under uncertainty is essential. His research continues to shape the future of intelligent manipulation systems.
Research Focus
Key Achievements
Top Papers
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- 2