Tangren Dan
Papers
1
Total Citations
7
H-Index
1
About
Tangren Dan is a researcher specializing in robotics motion planning and collision detection algorithms, with a particular focus on high-dimensional robotic systems operating in complex environments. His most cited work, "Design and implementation of improved RRT algorithm for collision free motion planning of high-dimensional robot in complex environment" (2012), has garnered 7 citations and introduces a novel enhancement to the Rapidly-exploring Random Tree (RRT) algorithm. Dan's major contribution lies in integrating an Oriented Bounding Box (OBB)-based collision detection method using the Separating Axis Theorem, which significantly improves computational efficiency and safety for robots navigating cluttered spaces. This work addresses critical challenges in autonomous navigation, enabling more reliable motion planning for high-degree-of-freedom manipulators and mobile robots. While his citation count reflects a focused but impactful contribution, Dan's research advances the practical deployment of robots in real-world settings, such as manufacturing and service environments. His algorithmic innovations provide a foundation for further developments in collision-free path planning, making his work a valuable reference for students and researchers exploring motion planning in complex, obstacle-rich domains.
Research Focus
Key Achievements
Top Papers
- 1