Papers
6
Total Citations
70
H-Index
5
About
Jiaxin Li is a leading researcher in brain-inspired robotics, with a primary focus on simultaneous localization and mapping (SLAM), cognitive robot systems, and autonomous navigation. Their most influential work, "A brain-inspired SLAM system based on ORB features" (2017, 32 citations), pioneered the integration of RatSLAM with modern visual features, enabling mobile robots to navigate more efficiently by mimicking hippocampal-entorhinal processing. This foundational contribution has shaped subsequent advances in biologically plausible SLAM. Li further refined loop closure detection in "A Hybrid Loop Closure Detection Method Based on Brain-Inspired Models" (2022, 11 citations), addressing a critical challenge in long-term robot localization. Their research also spans dynamic environment handling with DOC-SLAM (2021, 7 citations), which culls moving objects to improve stereo SLAM accuracy, and cognitive robotics through spiking neural networks that associate vision with action (2022, 8 citations). Most recently, Li developed a spiral coverage path planning algorithm for non-omnidirectional robots (2025, 8 citations), solving complex coverage tasks with reduced overlap. With a growing citation record and contributions spanning SLAM, grasping pipelines, and neural-inspired cognition, Jiaxin Li is shaping the future of autonomous, brain-like robotic intelligence.
Research Focus
Key Achievements
Top Papers
- 1A brain-inspired SLAM system based on ORB features32 citations · 2017
- 2A Hybrid Loop Closure Detection Method Based on Brain-Inspired Models11 citations · 2022
- 3A Spiral Coverage Path Planning Algorithm for Nonomnidirectional Robots8 citations · 2025
- 4
- 5DOC-SLAM: Robust Stereo SLAM with Dynamic Object Culling7 citations · 2021
- 6