Zhi‐Cheng Tan
Papers
1
Total Citations
2
H-Index
1
About
Zhi-Cheng Tan is a rising researcher in the field of robotics, with a primary focus on intelligent motion planning and autonomous navigation. His work centers on overcoming critical challenges in robotic arm manipulation, particularly in dynamic and obstacle-rich environments. Tan’s major contribution lies in advancing the Rapidly-exploring Random Tree (RRT) algorithm, a cornerstone of path planning. He has developed an improved RRT algorithm that directly addresses the conventional method’s shortcomings—namely, its tendency to produce non-smooth paths, low search efficiency, and poor adaptability in complex spaces. His most-cited paper, "Research on Obstacle Avoidance Path Planning for Robotic Arms Using Improved RRT Algorithm" (2025), has already garnered early attention with 2 citations, signaling its relevance to ongoing research. By enhancing path smoothness and search speed, Tan’s work provides a more practical and efficient solution for real-world robotic applications, from industrial automation to service robotics. As his research gains traction, Zhi-Cheng Tan is establishing himself as a thoughtful innovator in the quest for more agile and intelligent robotic systems.
Research Focus
Key Achievements
Top Papers
- 1