Papers
15
Total Citations
352
H-Index
10
About
Jikai Wang is a leading researcher in robotics and autonomous systems, specializing in Simultaneous Localization and Mapping (SLAM), visual and LiDAR-based navigation, and deep learning for mobile robotics. Their major contributions include developing DP-SLAM, a visual SLAM system that handles dynamic environments by incorporating moving probability, which has garnered 151 citations and become a key reference in the field. Wang has also advanced LiDAR SLAM with novel feature selection and three-stage loop closure optimization, achieving 26 citations, and proposed a CNN-based system for indoor robot navigation using small datasets, demonstrating practical applicability. Their work on probabilistic indoor global localization and hybrid map-based path planning has further enriched autonomous navigation. With over 300 total citations across ten highly cited papers, Wang’s research addresses critical challenges in real-world robotics, from dynamic scene understanding to efficient mapping. Their achievements include pioneering the use of regression forests for visual relocalization and developing MapSegNet for automated indoor map segmentation. Wang’s contributions are essential reading for anyone interested in robust, intelligent robotic navigation.
Research Focus
Key Achievements
Top Papers
- 1DP-SLAM: A visual SLAM with moving probability towards dynamic environments151 citations · 2021
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- 7A Review of Visual SLAM Based on Unmanned Systems16 citations · 2021
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- 9A Novel Hybrid Map Based Global Path Planning Method15 citations · 2018
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