Pengkai Wang

Papers

Total Citations

H-Index

About

Pengkai Wang is a researcher at the forefront of intelligent robotics, specializing in autonomous navigation, path planning, and aerial robot control in dynamic and constrained environments. His major contributions lie in developing adaptive and learning-based algorithms that enable robots—both ground and aerial—to operate safely and efficiently under real-world challenges. Wang’s most cited work, “ABA*–Adaptive Bidirectional A* Algorithm for Aerial Robot Path Planning” (2023, 18 citations), introduces a novel variant of the classic A* search that dynamically adjusts its heuristic to handle kinematic and physical constraints, achieving collision-free paths for drones. This work has been foundational for researchers tackling real-time autonomous guidance. More recently, Wang has pioneered the use of transformer architectures in robotics, as seen in his 2025 papers on transformer-based path planning for single-arm and dual-arm manipulators and aerial tracking systems that compensate for wind disturbances. These contributions highlight his ability to bridge classical planning with modern deep learning, offering robust solutions for complex, dynamic environments. Wang’s work is increasingly cited in the fields of aerial robotics, autonomous systems, and intelligent control, marking him as an emerging leader in adaptive robot navigation.