Pangcheng David Cen Cheng
Papers
12
Total Citations
218
H-Index
6
About
Pangcheng David Cen Cheng is a leading researcher in the fields of human-robot interaction, autonomous mobile robotics, and smart manufacturing. His work focuses on developing perception, path planning, and sensor fusion systems that enable safe, intuitive collaboration between humans and robots in industrial environments. His most cited paper, “Human-Robot Perception in Industrial Environments: A Survey” (152 citations), provides a comprehensive overview of perception capabilities critical for flexible, adaptive automation. Cen Cheng has pioneered multi-agent formation path planning and collision avoidance, as well as meta-sensor networks like Sen3Bot Net, which allow fleets of Autonomous Mobile Robots to act as distributed safety sensors in human-shared workspaces. He has also advanced dynamic path planning using costmap layers in ROS2 and supervised global planning with human-obstacle avoidance, addressing the core challenges of Industry 4.0 and 5.0. His recent work on low-resource mobile manipulators for safe object handling demonstrates a commitment to human-centric robotics. With over 200 total citations and a growing portfolio of high-impact publications, Cen Cheng’s research is shaping the future of safe, autonomous, and collaborative industrial systems.
Research Focus
Key Achievements
Top Papers
- 1Human-Robot Perception in Industrial Environments: A Survey152 citations · 2021
- 2Path planning in formation and collision avoidance for multi-agent systems12 citations · 2022
- 3Sensor data fusion for smart AMRs in human-shared industrial workspaces12 citations · 2019
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