Hengzhu Liu
Papers
10
Total Citations
96
H-Index
4
About
Hengzhu Liu is a robotics researcher whose work centers on multi-robot coverage path planning, motion planning, and autonomous navigation. Liu’s major contributions include developing exact and heuristic algorithms for multi-robot Dubins coverage path planning, enabling curvature-constrained robots to efficiently cover known environments for applications like aerial monitoring and search and rescue. Their 2023 paper on this topic has garnered 44 citations, reflecting its impact. Liu also addressed the challenge of coordinating robots with different velocities to achieve complete coverage, a problem tackled in their 2022 work (11 citations). In path planning, Liu introduced the "Late Line-of-Sight Check" method, which accelerates any-angle path planning on grid maps (10 citations), and extended this to sampling-based motion planning with tree structures. Notable achievements include work on collision-free coverage for variable-speed curvature-constrained robots and a convolutional neural network-based approach for coarse initial position estimation in large-scale 3D maps. Liu’s research bridges theoretical algorithm design with practical robotic systems, including a system-on-chip implementation of visual-inertial odometry for low-cost ground robots, demonstrating a commitment to deployable solutions.
Research Focus
Key Achievements
Top Papers
- 1
- 2Complete coverage problem of multiple robots with different velocities11 citations · 2022
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- 5Late Line-of-Sight Check and Prioritized Trees for Path Planning4 citations · 2019
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- 9Unsupervised Stereo Depth Estimation Refined by Perceptual Loss3 citations · 2018
- 10