Papers

4

Total Citations

36

H-Index

4

About

Aphilak Lonklang is a robotics researcher whose work centers on advancing mobile robot path planning and manipulator control. His primary contributions lie in improving the Rapidly Exploring Random Tree (RRT*) algorithm, a cornerstone of collision-free navigation. In his most cited work (21 citations), he introduced an "Improved RRT*" that incorporates bacterial mutation and node deletion, significantly enhancing offline path optimization. He further extended this to handle unknown static obstacles, a critical challenge for real-world autonomous navigation, and developed a variant that reduces random map size for greater computational efficiency. Beyond path planning, Lonklang has hands-on experience in robotic hardware, demonstrated by his prototyping of a 2-DOF robot arm with a feedback control system using DC motors and encoders. His research bridges theoretical algorithm design with practical implementation, addressing both global path planning and dynamic obstacle avoidance. With a growing citation record and a clear focus on making RRT-based algorithms more robust and efficient, Lonklang is contributing to the foundational tools that enable mobile robots to operate safely and autonomously in complex, unpredictable environments.

Research Focus

Key Achievements

4
H-Index
4
Papers
36
Total Citations
9
Avg Citations/Paper
🏆 Most Cited Paper
Improved Rapidly Exploring Random Tree with Bacterial Mutation and Node Deletion for Offline Path Planning of Mobile Robot
21 citations · 2022
📈 Most Prolific Year: 2022 (1 Papers)
🤝 Key Collaborators: 3
🏛 Institutions: Eötvös Loránd University, Suranaree University of Technology

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 17 days ago