Papers
10
Total Citations
112
H-Index
5
About
Zhengcheng Shen is a robotics researcher specializing in autonomous mobile robot navigation, deep reinforcement learning (DRL), and human-robot interaction in complex, dynamic environments. His work sits at the intersection of intelligent navigation systems, semantic perception, and social robotics, with a particular focus on making robots deployable in real-world crowded settings such as hospitals, airports, and logistics facilities. Shen's most influential contribution, "Arena-Rosnav" (2021, 50 citations), pioneered the integration of DRL-based obstacle avoidance into conventional ROS navigation stacks, bridging the gap between research and practical deployment. He further advanced socially aware navigation through semantic DRL frameworks for human-following and -guiding tasks (2022, 22 citations), and explored spatial imagination and memory-aided reinforcement learning to enhance robot perception and planning under uncertainty. His 2023 work on hybrid hierarchical navigation architectures addresses the limitations of standalone planners in highly dynamic scenarios, while the recently introduced Arena 4.0 platform (2025) provides a comprehensive ROS2 benchmarking environment powered by generative models for human-centric navigation research. With over 110 cumulative citations, Shen has established himself as a meaningful contributor to the mobile robotics community, consistently advancing the state of the art in safe, flexible, and socially intelligent robot navigation.
Research Focus
Key Achievements
Top Papers
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- 4Spatial Imagination With Semantic Cognition for Mobile Robots8 citations · 2021
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- 10Enhanced Neural SLAM with Semantic Segmentation in Dynamic Environments2 citations · 2023