Papers

7

Total Citations

340

H-Index

5

About

Xiaolin Dai is a robotics and autonomous systems researcher whose work spans mobile robot path planning, parallel robot manipulators, and advanced control strategies. His most influential contribution, a 2019 paper proposing a hybrid ant colony algorithm enhanced with A* heuristic methods for mobile robot path planning, has garnered over 215 citations, establishing him as a recognized voice in intelligent navigation. Building on this foundation, his 2020 follow-up work integrated Markov Decision Processes to generate smoother, safer trajectories in grid-based environments, earning an additional 62 citations and demonstrating his commitment to practical, high-quality autonomous navigation solutions. Beyond path planning, Dai has made meaningful contributions to parallel robot mechanics, including neural network compensation control for Gough-Stewart platforms under uncertain loads and Extended Kalman Filter-based load parameter identification — work that addresses real-world dynamic coupling challenges in robotic manipulation. His earlier kinematic analysis of 3-DOF rotational parallel mechanisms reflects a career grounded in rigorous mechanical theory. More recently, Dai has extended his research into fault-tolerant control for robotic manipulators and flexible control of rope-driven serpentine arms, signaling a broadening research vision. Across his body of work, Dai consistently bridges theoretical innovation with engineering applicability, making his research valuable to both robotics scholars and practitioners.

Research Focus

Key Achievements

5
H-Index
7
Papers
340
Total Citations
49
Avg Citations/Paper
🏆 Most Cited Paper
Mobile Robot Path Planning Based on Ant Colony Algorithm With A* Heuristic Method
215 citations · 2019
📈 Most Prolific Year: 2020 (2 Papers)
🤝 Key Collaborators: 17
🏛 Institutions: University of Electronic Science and Technology of China, Harbin Institute of Technology

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago