Zhanjie Chen

Guizhou University, Oklahoma State University

Papers

Total Citations

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About

Zhanjie Chen is a researcher at the forefront of social robotics and ambient assisted living, with a focus on enabling intelligent machines to seamlessly perceive and interact with human environments. His work bridges the critical gap between autonomous navigation and human-centric care, addressing fundamental challenges in how robots understand their surroundings and assist people in daily life. Chen’s major contributions lie in three interconnected areas: visual SLAM (Simultaneous Localization and Mapping) for social robots, multi-sensor fusion for smart home integration, and deep reinforcement learning for elderly care monitoring. His 2018 paper on comparing feature-based and direct methods in visual SLAM (10 citations) provided essential guidance for robot localization in unknown environments, while his work on a home assistant-based collaborative framework (7 citations) tackled the critical interoperability problem among smart home devices from different manufacturers. Most recently, Chen has pioneered the application of Deep Q-Learning to optimize activity monitoring for elderly care (2024), developing an intelligent system that balances activity recognition accuracy with privacy concerns, robot resource costs, and smartwatch power consumption. This innovative approach demonstrates his commitment to creating practical, ethical, and resource-efficient solutions for real-world deployment. With a growing citation impact and a clear trajectory toward human-centered AI, Chen’s research continues to shape the future of socially assistive robotics.