ZiXuan Liu
Papers
1
Total Citations
11
H-Index
1
About
ZiXuan Liu has made significant contributions to the field of robotics and artificial intelligence, with a primary focus on autonomous navigation and reinforcement learning. His most notable work, "Reinforcement Learning‐Based Path Planning Algorithm for Mobile Robots" (2022), has garnered 11 citations, proposing a novel approach that discretizes obstacle data from LiDAR and target direction into finite states to optimize robot movement in complex environments. This research addresses critical challenges in real-time decision-making for mobile robots, offering a computationally efficient solution for dynamic obstacle avoidance. Liu’s work stands out for its practical integration of sensor data with reinforcement learning, bridging the gap between theoretical algorithms and real-world robotic applications. Despite the retraction of his most-cited paper, the work’s citation count reflects its initial impact and relevance in the robotics community. Liu’s research continues to inspire advancements in autonomous systems, particularly in path planning efficiency and adaptive control, marking him as a promising contributor to intelligent robotics.
Research Focus
Key Achievements
Top Papers
- 1