Yibo Tan

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About

Yibo Tan is a researcher in robotics and autonomous navigation, with a primary focus on path planning and motion optimization for mobile robots. Their most influential work, "Path Planning of Mobile Robot Based on Improved PRM Based on Cubic Spline" (2022, 37 citations), addresses critical limitations in traditional Probabilistic Roadmap (PRM) algorithms—namely, low search efficiency and excessive path turning points. Tan introduced a bidirectional search PRM global path planning algorithm that enhances search connection rules by leveraging both forward and backward directions, significantly improving the smoothness and computational efficiency of generated paths. This contribution has practical implications for real-time robot navigation in complex environments. While still early in their career, Tan’s work demonstrates a clear commitment to advancing practical, computationally efficient solutions for autonomous systems. Their research is particularly relevant for students and engineers working on mobile robotics, autonomous vehicles, and intelligent transportation systems, offering a foundation for further exploration into sampling-based path planning and trajectory optimization.