W. Pengying
Papers
1
Total Citations
8
H-Index
1
About
W. Pengying is a rising researcher in robotics and autonomous systems, with a core focus on trajectory planning and target tracking in complex, cluttered environments. Their most-cited work, “Probabilistic Visibility-Aware Trajectory Planning for Target Tracking in Cluttered Environments” (2024, 8 citations), addresses a critical challenge in both civilian and military applications: maintaining continuous visual contact with a moving target despite obstacles and limited sensor fields of view. Pengying’s key contribution lies in developing probabilistic methods that explicitly model and optimize for target visibility during motion planning, moving beyond traditional approaches that treat visibility as a binary constraint. This work has already garnered attention for its practical relevance, offering a principled framework for drones or ground robots to autonomously track subjects through dense forests, urban canyons, or indoor spaces. By integrating uncertainty and sensor limitations directly into the planning process, Pengying’s research bridges the gap between theoretical path planning and real-world deployment. Their contributions are particularly timely as autonomous systems increasingly operate in human-centric environments, and their visibility-aware approach promises to enhance the reliability of applications ranging from search-and-rescue to surveillance.
Research Focus
Key Achievements
Top Papers
- 1