Papers

3

Total Citations

41

H-Index

3

About

Dianyuan Ju is a robotics researcher whose work focuses on advancing path planning algorithms for autonomous mobile robots operating in static, two-dimensional environments. His primary contributions lie in improving the efficiency, safety, and smoothness of Rapidly-exploring Random Tree (RRT) based planners. Ju’s most influential work, "CAF-RRT*: A 2D Path Planning Algorithm Based on Circular Arc Fillet Method" (2022, 20 citations), introduces a novel method that combines Quick-RRT* with bidirectional search and a circular arc fillet technique to generate smoother, more feasible paths. He further refined this approach with "Bi-RRT*: An Improved Bidirectional RRT* Path Planner for Robot in Two-Dimensional Space" (2023, 17 citations), which enhances convergence speed and solution quality. Addressing practical concerns of safety and energy efficiency, Ju also proposed "SS-RRT*: A Safe and Smoothing Path Planner for Mobile Robot in Static Environment" (2022, 4 citations), which integrates a hybrid strategy to minimize collision risk and energy loss. Collectively, his work has garnered over 40 citations, establishing him as a contributor to the practical deployment of sampling-based planners. By tackling the trade-offs between computational speed, path optimality, and real-world applicability, Ju’s algorithms offer tangible improvements for robotic navigation in cluttered spaces.

Research Focus

Key Achievements

3
H-Index
3
Papers
41
Total Citations
14
Avg Citations/Paper
🏆 Most Cited Paper
CAF-RRT<sup>*</sup>: A 2D Path Planning Algorithm Based on Circular Arc Fillet Method
20 citations · 2022
📈 Most Prolific Year: 2022 (2 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: Qilu University of Technology, Shandong Academy of Sciences

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago